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2020 – today
- 2025
[j143]Deyi Ji
, Feng Zhao, Hongtao Lu, Feng Wu, Jieping Ye:
Structural and Statistical Texture Knowledge Distillation and Learning for Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 47(5): 3639-3656 (2025)- [j142]Tianxiang Chen, Zhentao Tan, Tao Gong, Qi Chu, Yue Wu, Bin Liu, Nenghai Yu, Le Lu, Jieping Ye:
Bootstrapping Audio-Visual Video Segmentation by Strengthening Audio Cues. IEEE Trans. Circuits Syst. Video Technol. 35(3): 2398-2409 (2025) - [j141]Kai Liu, Zhihang Fu, Sheng Jin, Ze Chen, Fan Zhou, Rongxin Jiang, Yaowu Chen, Jieping Ye:
ESOD: Efficient Small Object Detection on High-Resolution Images. IEEE Trans. Image Process. 34: 183-195 (2025) - [j140]Lanyun Zhu, Tianrun Chen, Deyi Ji, Jieping Ye, Jun Liu:
Not Every Patch is Needed: Toward a More Efficient and Effective Backbone for Video-Based Person Re-Identification. IEEE Trans. Image Process. 34: 785-800 (2025) - [j139]Junjie Liu, Junlong Liu, Rongxin Jiang, Yaowu Chen, Chen Shen, Jieping Ye:
Self-Learning Symmetric Multi-View Probabilistic Clustering. IEEE Trans. Knowl. Data Eng. 37(4): 2097-2110 (2025) - [c296]Xiao Han, Zijian Zhang, Xiangyu Zhao, Yuanshao Zhu, Guojiang Shen, Xiangjie Kong, Xuetao Wei, Liqiang Nie, Jieping Ye:
GARLIC: GPT-Augmented Reinforcement Learning with Intelligent Control for Vehicle Dispatching. AAAI 2025: 255-263 - [c295]Hanzhu Chen, Xu Shen, Jie Wang, Zehao Wang, Qitan Lv, Junjie He, Rong Wu, Feng Wu, Jieping Ye:
Knowledge Graph Finetuning Enhances Knowledge Manipulation in Large Language Models. ICLR 2025 - [c294]Rui Dai, Sile Hu, Xu Shen, Yonggang Zhang, Xinmei Tian, Jieping Ye:
Leveraging Submodule Linearity Enhances Task Arithmetic Performance in LLMs. ICLR 2025 - [c293]Sinan Fan, Liang Xie, Chen Shen, Ge Teng, Xiaosong Yuan, Xiaofeng Zhang, Chenxi Huang, Wenxiao Wang, Xiaofei He, Jieping Ye:
Improving Complex Reasoning with Dynamic Prompt Corruption: A Soft Prompt Optimization Approach. ICLR 2025 - [c292]Yang Qin, Chao Chen, Zhihang Fu, Ze Chen, Dezhong Peng, Peng Hu, Jieping Ye:
ROUTE: Robust Multitask Tuning and Collaboration for Text-to-SQL. ICLR 2025 - [c291]Shaotian Yan, Chen Shen, Wenxiao Wang, Liang Xie, Junjie Liu, Jieping Ye:
Don't Take Things Out of Context: Attention Intervention for Enhancing Chain-of-Thought Reasoning in Large Language Models. ICLR 2025 - [c290]Junjie Liu, Shaotian Yan, Chen Shen, Zhengdong Xiao, Liang Xie, Wenxiao Wang, Jieping Ye:
Concise and Organized Perception Facilitates Reasoning in Large Language Models. NAACL (Findings) 2025: 3469-3498 - [i155]Lanyun Zhu, Tianrun Chen, Deyi Ji, Jieping Ye, Jun Liu:
Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification. CoRR abs/2501.16811 (2025) - [i154]Wei Wu, Qiuyi Li, Mingyang Li, Kun Fu, Fuli Feng, Jieping Ye, Hui Xiong, Zheng Wang:
GENERator: A Long-Context Generative Genomic Foundation Model. CoRR abs/2502.07272 (2025) - [i153]Chenghao Zhang, Lubin Fan, Shen Cao, Bojian Wu, Jieping Ye:
CoL3D: Collaborative Learning of Single-view Depth and Camera Intrinsics for Metric 3D Shape Recovery. CoRR abs/2502.08902 (2025) - [i152]Jinhui Guo, Lubin Fan, Bojian Wu, Jiaqi Gu, Shen Cao, Jieping Ye:
PTZ-Calib: Robust Pan-Tilt-Zoom Camera Calibration. CoRR abs/2502.09075 (2025) - [i151]Dongbo Shi, Shen Cao, Lubin Fan, Bojian Wu, Jinhui Guo, Renjie Chen, Ligang Liu, Jieping Ye:
No Parameters, No Problem: 3D Gaussian Splatting without Camera Intrinsics and Extrinsics. CoRR abs/2502.19800 (2025) - [i150]Tong Ge, Yashu Liu, Jieping Ye, Tianyi Li, Chao Wang:
Advancing vision-language models in front-end development via data synthesis. CoRR abs/2503.01619 (2025) - [i149]Yiheng Zhu, Mingyang Li, Junlong Liu, Kun Fu, Jiansheng Wu, Qiuyi Li, Mingze Yin, Jieping Ye, Jian Wu, Zheng Wang:
A Generalist Cross-Domain Molecular Learning Framework for Structure-Based Drug Discovery. CoRR abs/2503.04362 (2025) - [i148]Deyi Ji, Feng Zhao, Hongtao Lu, Feng Wu, Jieping Ye:
Structural and Statistical Texture Knowledge Distillation and Learning for Segmentation. CoRR abs/2503.08043 (2025) - [i147]Shaotian Yan, Chen Shen, Wenxiao Wang, Liang Xie, Junjie Liu, Jieping Ye:
Don't Take Things Out of Context: Attention Intervention for Enhancing Chain-of-Thought Reasoning in Large Language Models. CoRR abs/2503.11154 (2025) - [i146]Sinan Fan, Liang Xie, Chen Shen, Ge Teng, Xiaosong Yuan, Xiaofeng Zhang, Chenxi Huang, Wenxiao Wang, Xiaofei He, Jieping Ye:
Improving Complex Reasoning with Dynamic Prompt Corruption: A soft prompt Optimization Approach. CoRR abs/2503.13208 (2025) - [i145]He Zhu, Quyu Kong, Kechun Xu, Xunlong Xia, Bing Deng, Jieping Ye, Rong Xiong, Yue Wang:
Grounding 3D Object Affordance with Language Instructions, Visual Observations and Interactions. CoRR abs/2504.04744 (2025) - 2024
- [j138]Tingjin Luo, Yang Yang, Dongyun Yi, Jieping Ye:
Robust discriminative feature learning with calibrated data reconstruction and sparse low-rank model. Appl. Intell. 54(3): 2867-2880 (2024) - [j137]Zhihao Shi, Jie Wang, Fanghua Lu, Hanzhu Chen, Defu Lian, Zheng Wang, Jieping Ye, Feng Wu:
Label Deconvolution for Node Representation Learning on Large-Scale Attributed Graphs Against Learning Bias. IEEE Trans. Pattern Anal. Mach. Intell. 46(12): 11273-11286 (2024) - [j136]Yunkai Wang, Quyu Kong, He Zhu, Dongkun Zhang, Longzhong Lin, Hao Sha, Xunlong Xia, Qiao Liang, Bing Deng, Ken Chen, Rong Xiong, Yue Wang, Jieping Ye:
Enhancing Closed-Loop Performance in Learning-Based Vehicle Motion Planning by Integrating Rule-Based Insights. IEEE Robotics Autom. Lett. 9(9): 7915-7922 (2024) - [j135]Hanqing Yang, Sijia Cai, Bing Deng, Jieping Ye, Guosheng Lin, Yu Zhang:
Context-Aware and Semantic-Consistent Spatial Interactions for One-Shot Object Detection Without Fine-Tuning. IEEE Trans. Circuits Syst. Video Technol. 34(7): 5424-5439 (2024) - [j134]Tianxiang Chen, Zi Ye, Zhentao Tan, Tao Gong, Yue Wu, Qi Chu, Bin Liu, Nenghai Yu, Jieping Ye:
MiM-ISTD: Mamba-in-Mamba for Efficient Infrared Small-Target Detection. IEEE Trans. Geosci. Remote. Sens. 62: 1-13 (2024) - [j133]Zhentao Tan, Yue Wu, Qiankun Liu, Qi Chu, Le Lu, Jieping Ye, Nenghai Yu:
Exploring the Application of Large-Scale Pre-Trained Models on Adverse Weather Removal. IEEE Trans. Image Process. 33: 1683-1698 (2024) - [j132]Langzhang Liang, Zenglin Xu, Zixing Song, Irwin King, Yuan Qi, Jieping Ye:
Tackling Long-Tailed Distribution Issue in Graph Neural Networks via Normalization. IEEE Trans. Knowl. Data Eng. 36(5): 2213-2223 (2024) - [j131]Haomin Wen, Youfang Lin, Lixia Wu, Xiaowei Mao, Tianyue Cai, Yunfeng Hou, Shengnan Guo, Yuxuan Liang, Guangyin Jin, Yiji Zhao, Roger Zimmermann, Jieping Ye, Huaiyu Wan:
A Survey on Service Route and Time Prediction in Instant Delivery: Taxonomy, Progress, and Prospects. IEEE Trans. Knowl. Data Eng. 36(12): 7516-7535 (2024) - [j130]Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang:
Stochastic gradient descent without full data shuffle: with applications to in-database machine learning and deep learning systems. VLDB J. 33(5): 1231-1255 (2024) - [c289]Hanzhu Chen, Xu Shen, Qitan Lv, Jie Wang, Xiaoqi Ni, Jieping Ye:
SAC-KG: Exploiting Large Language Models as Skilled Automatic Constructors for Domain Knowledge Graph. ACL (1) 2024: 4345-4360 - [c288]Lanyun Zhu, Tianrun Chen, Deyi Ji, Jieping Ye, Jun Liu:
LLaFS: When Large Language Models Meet Few-Shot Segmentation. CVPR 2024: 3065-3075 - [c287]Wei Zhang, Chaoqun Wan, Tongliang Liu, Xinmei Tian, Xu Shen, Jieping Ye:
Enhanced Motion-Text Alignment for Image-to-Video Transfer Learning. CVPR 2024: 18504-18515 - [c286]Shixiong Xu, Chenghao Zhang, Lubin Fan, Gaofeng Meng, Shiming Xiang, Jieping Ye:
AddressCLIP: Empowering Vision-Language Models for City-Wide Image Address Localization. ECCV (28) 2024: 76-92 - [c285]Jingyu Lin, Jiaqi Gu, Bojian Wu, Lubin Fan, Renjie Chen, Ligang Liu, Jieping Ye:
Learning Neural Volumetric Pose Features for Camera Localization. ECCV (45) 2024: 198-214 - [c284]Xiaosu Zhu, Hualian Sheng, Sijia Cai, Bing Deng, Shaopeng Yang, Qiao Liang, Ken Chen, Lianli Gao, Jingkuan Song, Jieping Ye:
RoScenes: A Large-Scale Multi-view 3D Dataset for Roadside Perception. ECCV (41) 2024: 331-347 - [c283]Tianxiang Chen, Zhentao Tan, Tao Gong, Yue Wu, Qi Chu, Bin Liu, Jieping Ye, Nenghai Yu:
Llama SLayer 8B: Shallow Layers Hold the Key to Knowledge Injection. EMNLP (Findings) 2024: 5991-6002 - [c282]Wei Li, Zhen Huang, Xinmei Tian, Le Lu, Houqiang Li, Xu Shen, Jieping Ye:
Interpretable Composition Attribution Enhancement for Visio-linguistic Compositional Understanding. EMNLP 2024: 14616-14632 - [c281]Chao Chen, Kai Liu, Ze Chen, Yi Gu, Yue Wu, Mingyuan Tao, Zhihang Fu, Jieping Ye:
INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection. ICLR 2024 - [c280]Dingyuan Shi, Yongxin Tong, Zimu Zhou, Ke Xu, Zheng Wang, Jieping Ye:
Graph-constrained diffusion for End-to-End Path Planning. ICLR 2024 - [c279]Zhentao Tan, Xiaodan Li, Yue Wu, Qi Chu, Le Lu, Nenghai Yu, Jieping Ye:
Boosting Vanilla Lightweight Vision Transformers via Re-parameterization. ICLR 2024 - [c278]Wei Chen, Zhen Huang, Liang Xie, Binbin Lin, Houqiang Li, Le Lu, Xinmei Tian, Deng Cai, Yonggang Zhang, Wenxiao Wang, Xu Shen, Jieping Ye:
From Yes-Men to Truth-Tellers: Addressing Sycophancy in Large Language Models with Pinpoint Tuning. ICML 2024 - [c277]Xun Deng, Junlong Liu, Han Zhong, Fuli Feng, Chen Shen, Xiangnan He, Jieping Ye, Zheng Wang:
A3S: A General Active Clustering Method with Pairwise Constraints. ICML 2024 - [c276]Deyi Ji, Feng Zhao, Lanyun Zhu, Wenwei Jin, Hongtao Lu, Jieping Ye:
Discrete Latent Perspective Learning for Segmentation and Detection. ICML 2024 - [c275]Wei Zhang, Chaoqun Wan, Yonggang Zhang, Yiu-ming Cheung, Xinmei Tian, Xu Shen, Jieping Ye:
Interpreting and Improving Large Language Models in Arithmetic Calculation. ICML 2024 - [c274]Weizhong Zhang, Zhiwei Zhang, Renjie Pi, Zhongming Jin, Yuan Gao, Jieping Ye, Kani Chen:
Efficient Denoising Diffusion via Probabilistic Masking. ICML 2024 - [c273]Ge Teng, Ting Mao, Chen Shen, Xiang Tian, Xuesong Liu, Yaowu Chen, Jieping Ye:
URRL-IMVC: Unified and Robust Representation Learning for Incomplete Multi-View Clustering. KDD 2024: 2888-2899 - [c272]Zhe Jiang, Liang Zhao, Xun Zhou, Junbo Zhang, Shashi Shekhar, Jieping Ye:
The 4th KDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems (DeepSpatial'24). KDD 2024: 6722-6723 - [c271]Yuxuan Liang, Chuishi Meng, Yanhua Li, Yu Zheng, Jieping Ye, Qiang Yang, Philip S. Yu, Ouri Wolfson:
The 13th International Workshop on Urban Computing. KDD 2024: 6727-6728 - [c270]Liyi Chen, Panrong Tong, Zhongming Jin, Ying Sun, Jieping Ye, Hui Xiong:
Plan-on-Graph: Self-Correcting Adaptive Planning of Large Language Model on Knowledge Graphs. NeurIPS 2024 - [c269]Zhengkai Lin, Zhihang Fu, Kai Liu, Liang Xie, Binbin Lin, Wenxiao Wang, Deng Cai, Yue Wu, Jieping Ye:
Delving into the Reversal Curse: How Far Can Large Language Models Generalize? NeurIPS 2024 - [c268]Kai Liu, Zhihang Fu, Sheng Jin, Chao Chen, Ze Chen, Rongxin Jiang, Fan Zhou, Yaowu Chen, Jieping Ye:
Rethinking Out-of-Distribution Detection on Imbalanced Data Distribution. NeurIPS 2024 - [c267]Kai Liu, Zhihang Fu, Chao Chen, Wei Zhang, Rongxin Jiang, Fan Zhou, Yaowu Chen, Yue Wu, Jieping Ye:
Enhancing LLM's Cognition via Structurization. NeurIPS 2024 - [c266]Yuxin Xiao, Chaoqun Wan, Yonggang Zhang, Wenxiao Wang, Binbin Lin, Xiaofei He, Xu Shen, Jieping Ye:
Enhancing Multiple Dimensions of Trustworthiness in LLMs via Sparse Activation Control. NeurIPS 2024 - [c265]Xiaosong Yuan, Chen Shen, Shaotian Yan, Xiaofeng Zhang, Liang Xie, Wenxiao Wang, Renchu Guan, Ying Wang, Jieping Ye:
Instance-adaptive Zero-shot Chain-of-Thought Prompting. NeurIPS 2024 - [c264]Yiheng Zhu, Jialu Wu, Qiuyi Li, Jiahuan Yan, Mingze Yin, Wei Wu, Mingyang Li, Jieping Ye, Zheng Wang, Jian Wu:
Bridge-IF: Learning Inverse Protein Folding with Markov Bridges. NeurIPS 2024 - [i144]Tianxiang Chen, Zhentao Tan, Tao Gong, Qi Chu, Yue Wu, Bin Liu, Le Lu, Jieping Ye, Nenghai Yu:
Bootstrapping Audio-Visual Segmentation by Strengthening Audio Cues. CoRR abs/2402.02327 (2024) - [i143]Chao Chen, Kai Liu, Ze Chen, Yi Gu, Yue Wu, Mingyuan Tao, Zhihang Fu, Jieping Ye:
INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection. CoRR abs/2402.03744 (2024) - [i142]Chao Chen, Zhihang Fu, Kai Liu, Ze Chen, Mingyuan Tao, Jieping Ye:
Optimal Parameter and Neuron Pruning for Out-of-Distribution Detection. CoRR abs/2402.10062 (2024) - [i141]Lanyun Zhu, Deyi Ji, Tianrun Chen, Peng Xu, Jieping Ye, Jun Liu:
IBD: Alleviating Hallucinations in Large Vision-Language Models via Image-Biased Decoding. CoRR abs/2402.18476 (2024) - [i140]Tianxiang Chen, Zhentao Tan, Tao Gong, Qi Chu, Yue Wu, Bin Liu, Jieping Ye, Nenghai Yu:
MiM-ISTD: Mamba-in-Mamba for Efficient Infrared Small Target Detection. CoRR abs/2403.02148 (2024) - [i139]Jingyu Lin, Jiaqi Gu, Bojian Wu, Lubin Fan, Renjie Chen, Ligang Liu, Jieping Ye:
Learning Neural Volumetric Pose Features for Camera Localization. CoRR abs/2403.12800 (2024) - [i138]Xize Liang, Chao Chen, Jie Wang, Yue Wu, Zhihang Fu, Zhihao Shi, Feng Wu, Jieping Ye:
Robust Preference Optimization with Provable Noise Tolerance for LLMs. CoRR abs/2404.04102 (2024) - [i137]Xiaosu Zhu, Hualian Sheng, Sijia Cai, Bing Deng, Shaopeng Yang, Qiao Liang, Ken Chen, Lianli Gao, Jingkuan Song, Jieping Ye:
RoScenes: A Large-scale Multi-view 3D Dataset for Roadside Perception. CoRR abs/2405.09883 (2024) - [i136]Peng Li, Lixia Wu, Chaoqun Feng, Haoyuan Hu, Lei Fu, Jieping Ye:
Differentiation of Multi-objective Data-driven Decision Pipeline. CoRR abs/2406.00779 (2024) - [i135]Xiaofeng Zhang, Chen Shen, Xiaosong Yuan, Shaotian Yan, Liang Xie, Wenxiao Wang, Chaochen Gu, Hao Tang, Jieping Ye:
From Redundancy to Relevance: Enhancing Explainability in Multimodal Large Language Models. CoRR abs/2406.06579 (2024) - [i134]Hualian Sheng, Sijia Cai, Na Zhao, Bing Deng, Qiao Liang, Min-Jian Zhao, Jieping Ye:
CT3D++: Improving 3D Object Detection with Keypoint-induced Channel-wise Transformer. CoRR abs/2406.08152 (2024) - [i133]Deyi Ji, Feng Zhao, Lanyun Zhu, Wenwei Jin, Hongtao Lu, Jieping Ye:
Discrete Latent Perspective Learning for Segmentation and Detection. CoRR abs/2406.10475 (2024) - [i132]Jinhua Zhang, Hualian Sheng, Sijia Cai, Bing Deng, Qiao Liang, Wen Li, Ying Fu, Jieping Ye, Shuhang Gu:
PerlDiff: Controllable Street View Synthesis Using Perspective-Layout Diffusion Models. CoRR abs/2407.06109 (2024) - [i131]Shixiong Xu, Chenghao Zhang, Lubin Fan, Gaofeng Meng, Shiming Xiang, Jieping Ye:
AddressCLIP: Empowering Vision-Language Models for City-wide Image Address Localization. CoRR abs/2407.08156 (2024) - [i130]Ge Teng, Ting Mao, Chen Shen, Xiang Tian, Xuesong Liu, Yaowu Chen, Jieping Ye:
URRL-IMVC: Unified and Robust Representation Learning for Incomplete Multi-View Clustering. CoRR abs/2407.09120 (2024) - [i129]Xun Deng, Junlong Liu, Han Zhong, Fuli Feng, Chen Shen, Xiangnan He, Jieping Ye, Zheng Wang:
A3S: A General Active Clustering Method with Pairwise Constraints. CoRR abs/2407.10196 (2024) - [i128]Kai Liu, Zhihang Fu, Sheng Jin, Ze Chen, Fan Zhou, Rongxin Jiang, Yaowu Chen, Jieping Ye:
ESOD: Efficient Small Object Detection on High-Resolution Images. CoRR abs/2407.16424 (2024) - [i127]Kai Liu, Zhihang Fu, Sheng Jin, Chao Chen, Ze Chen, Rongxin Jiang, Fan Zhou, Yaowu Chen, Jieping Ye:
Rethinking Out-of-Distribution Detection on Imbalanced Data Distribution. CoRR abs/2407.16430 (2024) - [i126]Kai Liu, Zhihang Fu, Chao Chen, Wei Zhang, Rongxin Jiang, Fan Zhou, Yaowu Chen, Yue Wu, Jieping Ye:
Enhancing LLM's Cognition via Structurization. CoRR abs/2407.16434 (2024) - [i125]Kai Liu, Ze Chen, Zhihang Fu, Rongxin Jiang, Fan Zhou, Yaowu Chen, Yue Wu, Jieping Ye:
Educating LLMs like Human Students: Structure-aware Injection of Domain Knowledge. CoRR abs/2407.16724 (2024) - [i124]Kai Liu, Zhihang Fu, Chao Chen, Sheng Jin, Ze Chen, Mingyuan Tao, Rongxin Jiang, Jieping Ye:
Category-Extensible Out-of-Distribution Detection via Hierarchical Context Descriptions. CoRR abs/2407.16725 (2024) - [i123]Xiao Han, Zijian Zhang, Xiangyu Zhao, Guojiang Shen, Xiangjie Kong, Xuetao Wei, Liqiang Nie, Jieping Ye:
GPT-Augmented Reinforcement Learning with Intelligent Control for Vehicle Dispatching. CoRR abs/2408.10286 (2024) - [i122]Wei Chen, Zhen Huang, Liang Xie, Binbin Lin, Houqiang Li, Le Lu, Xinmei Tian, Deng Cai, Yonggang Zhang, Wenxiao Wang, Xu Shen, Jieping Ye:
From Yes-Men to Truth-Tellers: Addressing Sycophancy in Large Language Models with Pinpoint Tuning. CoRR abs/2409.01658 (2024) - [i121]Wei Zhang, Chaoqun Wan, Yonggang Zhang, Yiu-ming Cheung, Xinmei Tian, Xu Shen, Jieping Ye:
Interpreting and Improving Large Language Models in Arithmetic Calculation. CoRR abs/2409.01659 (2024) - [i120]Xiaosong Yuan, Chen Shen, Shaotian Yan, Xiaofeng Zhang, Liang Xie, Wenxiao Wang, Renchu Guan, Ying Wang, Jieping Ye:
Instance-adaptive Zero-shot Chain-of-Thought Prompting. CoRR abs/2409.20441 (2024) - [i119]Tianxiang Chen, Zhentao Tan, Tao Gong, Yue Wu, Qi Chu, Bin Liu, Jieping Ye, Nenghai Yu:
Llama SLayer 8B: Shallow Layers Hold the Key to Knowledge Injection. CoRR abs/2410.02330 (2024) - [i118]Hanzhu Chen, Xu Shen, Qitan Lv, Jie Wang, Xiaoqi Ni, Jieping Ye:
SAC-KG: Exploiting Large Language Models as Skilled Automatic Constructors for Domain Knowledge Graphs. CoRR abs/2410.02811 (2024) - [i117]Wei Wu, Chao Wang, Liyi Chen, Mingze Yin, Yiheng Zhu, Kun Fu, Jieping Ye, Hui Xiong, Zheng Wang:
Structure-Enhanced Protein Instruction Tuning: Towards General-Purpose Protein Understanding. CoRR abs/2410.03553 (2024) - [i116]Zhengkai Lin, Zhihang Fu, Kai Liu, Liang Xie, Binbin Lin, Wenxiao Wang, Deng Cai, Yue Wu, Jieping Ye:
Delving into the Reversal Curse: How Far Can Large Language Models Generalize? CoRR abs/2410.18808 (2024) - [i115]Wenxiao Wang, Lihui Gu, Liye Zhang, Yunxiang Luo, Yi Dai, Chen Shen, Liang Xie, Binbin Lin, Xiaofei He, Jieping Ye:
SciPIP: An LLM-based Scientific Paper Idea Proposer. CoRR abs/2410.23166 (2024) - [i114]Liyi Chen, Panrong Tong, Zhongming Jin, Ying Sun, Jieping Ye, Hui Xiong:
Plan-on-Graph: Self-Correcting Adaptive Planning of Large Language Model on Knowledge Graphs. CoRR abs/2410.23875 (2024) - [i113]Yiheng Zhu, Jialu Wu, Qiuyi Li, Jiahuan Yan, Mingze Yin, Wei Wu, Mingyang Li, Jieping Ye, Zheng Wang, Jian Wu:
Bridge-IF: Learning Inverse Protein Folding with Markov Bridges. CoRR abs/2411.02120 (2024) - [i112]Yuxin Xiao, Chaoqun Wan, Yonggang Zhang, Wenxiao Wang, Binbin Lin, Xiaofei He, Xu Shen, Jieping Ye:
Enhancing Multiple Dimensions of Trustworthiness in LLMs via Sparse Activation Control. CoRR abs/2411.02461 (2024) - [i111]Deyi Ji, Lanyun Zhu, Siqi Gao, Peng Xu, Hongtao Lu, Jieping Ye, Feng Zhao:
Tree-of-Table: Unleashing the Power of LLMs for Enhanced Large-Scale Table Understanding. CoRR abs/2411.08516 (2024) - [i110]Xiaofeng Zhang, Yihao Quan, Chaochen Gu, Chen Shen, Xiaosong Yuan, Shaotian Yan, Hao Cheng, Kaijie Wu, Jieping Ye:
Seeing Clearly by Layer Two: Enhancing Attention Heads to Alleviate Hallucination in LVLMs. CoRR abs/2411.09968 (2024) - [i109]Jingyu Lin, Jiaqi Gu, Lubin Fan, Bojian Wu, Yujing Lou, Renjie Chen, Ligang Liu, Jieping Ye:
HybridGS: Decoupling Transients and Statics with 2D and 3D Gaussian Splatting. CoRR abs/2412.03844 (2024) - [i108]Yang Qin, Chao Chen, Zhihang Fu, Ze Chen, Dezhong Peng, Peng Hu, Jieping Ye:
ROUTE: Robust Multitask Tuning and Collaboration for Text-to-SQL. CoRR abs/2412.10138 (2024) - 2023
- [j129]Wei Ai, Yan Chen, Qiaozhu Mei, Jieping Ye, Lingyu Zhang:
Putting Teams into the Gig Economy: A Field Experiment at a Ride-Sharing Platform. Manag. Sci. 69(9): 5336-5353 (2023) - [j128]Xiong-Hui Chen, Fan-Ming Luo, Yang Yu, Qingyang Li, Zhiwei Qin, Wenjie Shang, Jieping Ye:
Offline Model-Based Adaptable Policy Learning for Decision-Making in Out-of-Support Regions. IEEE Trans. Pattern Anal. Mach. Intell. 45(12): 15260-15274 (2023) - [j127]Zhengxia Zou, Keyan Chen, Zhenwei Shi, Yuhong Guo, Jieping Ye:
Object Detection in 20 Years: A Survey. Proc. IEEE 111(3): 257-276 (2023) - [j126]Jiang Lu, Pinghua Gong, Jieping Ye, Jianwei Zhang, Changshui Zhang:
A survey on machine learning from few samples. Pattern Recognit. 139: 109480 (2023) - [j125]Jie Gui, Zhenan Sun, Yonggang Wen, Dacheng Tao, Jieping Ye:
A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications. IEEE Trans. Knowl. Data Eng. 35(4): 3313-3332 (2023) - [c263]Linzhi Huang, Yulong Li, Hongbo Tian, Yue Yang, Xiangang Li, Weihong Deng, Jieping Ye:
Semi-Supervised 2D Human Pose Estimation Driven by Position Inconsistency Pseudo Label Correction Module. CVPR 2023: 693-703 - [c262]Deyi Ji, Feng Zhao, Hongtao Lu, Mingyuan Tao, Jieping Ye:
Ultra-High Resolution Segmentation with Ultra-Rich Context: A Novel Benchmark. CVPR 2023: 23621-23630 - [c261]Han Yang, Fei Gu, Jieping Ye:
Rethinking Learning-Based Method for Lossless Genome Compression. ICASSP 2023: 1-5 - [c260]Kai Liu, Sheng Jin, Zhihang Fu, Ze Chen, Rongxin Jiang, Jieping Ye:
Uncertainty-aware Unsupervised Multi-Object Tracking. ICCV 2023: 9962-9971 - [c259]Shuyue Wei, Yongxin Tong, Zimu Zhou, Qiaoyang Liu, Lulu Zhang, Yuxiang Zeng, Jieping Ye:
Towards Capacity-Aware Broker Matching: From Recommendation to Assignment. ICDE 2023: 776-788 - [c258]Xiong-Hui Chen, Bowei He, Yang Yu, Qingyang Li, Zhiwei Tony Qin, Wenjie Shang, Jieping Ye, Chen Ma:
Sim2Rec: A Simulator-based Decision-making Approach to Optimize Real-World Long-term User Engagement in Sequential Recommender Systems. ICDE 2023: 3389-3402 - [c257]Chuishi Meng, Yanhua Li, Yu Zheng, Jieping Ye, Qiang Yang, Philip S. Yu, Ouri Wolfson:
The 12th International Workshop on Urban Computing. KDD 2023: 5874-5875 - [c256]Zhiwei (Tony) Qin, Rui Song, Jieping Ye, Hongtu Zhu, Michael I. Jordan:
KDD-2023 Workshop on Decision Intelligence and Analytics for Online Marketplaces. KDD 2023: 5878-5879 - [c255]Chao Chen, Zhihang Fu, Kai Liu, Ze Chen, Mingyuan Tao, Jieping Ye:
Optimal Parameter and Neuron Pruning for Out-of-Distribution Detection. NeurIPS 2023 - [c254]Kai Liu, Zhihang Fu, Chao Chen, Sheng Jin, Ze Chen, Mingyuan Tao, Rongxin Jiang, Jieping Ye:
Category-Extensible Out-of-Distribution Detection via Hierarchical Context Descriptions. NeurIPS 2023 - [c253]Yiheng Zhu, Yang Zhan, Xuankun Huang, Yuwei Chen, Yujie Chen, Jiangwen Wei, Wei Feng, Yinzhi Zhou, Haoyuan Hu, Jieping Ye:
OFCOURSE: A Multi-Agent Reinforcement Learning Environment for Order Fulfillment. NeurIPS 2023 - [e4]Ambuj K. Singh, Yizhou Sun, Leman Akoglu, Dimitrios Gunopulos, Xifeng Yan, Ravi Kumar, Fatma Ozcan, Jieping Ye:
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2023, Long Beach, CA, USA, August 6-10, 2023. ACM 2023 [contents] - [i107]Shuyue Wei, Yongxin Tong, Zimu Zhou, Qiaoyang Liu, Lulu Zhang, Yuxiang Zeng, Jieping Ye:
Towards Capacity-Aware Broker Matching: From Recommendation to Assignment. CoRR abs/2303.03024 (2023) - [i106]Linzhi Huang, Yulong Li, Hongbo Tian, Yue Yang, Xiangang Li, Weihong Deng, Jieping Ye:
Semi-Supervised 2D Human Pose Estimation Driven by Position Inconsistency Pseudo Label Correction Module. CoRR abs/2303.04346 (2023) - [i105]Xiong-Hui Chen, Bowei He, Yang Yu, Qingyang Li, Zhiwei Tony Qin, Wenjie Shang, Jieping Ye, Chen Ma:
Sim2Rec: A Simulator-based Decision-making Approach to Optimize Real-World Long-term User Engagement in Sequential Recommender Systems. CoRR abs/2305.04832 (2023) - [i104]Junjie Liu, Junlong Liu, Rongxin Jiang, Xuesong Liu, Boxuan Gu, Yaowu Chen, Chen Shen, Jieping Ye:
Self-Learning Symmetric Multi-view Probabilistic Clustering. CoRR abs/2305.07307 (2023) - [i103]Deyi Ji, Feng Zhao, Hongtao Lu, Mingyuan Tao, Jieping Ye:
Ultra-High Resolution Segmentation with Ultra-Rich Context: A Novel Benchmark. CoRR abs/2305.10899 (2023) - [i102]Zhentao Tan, Yue Wu, Qiankun Liu, Qi Chu, Le Lu, Jieping Ye, Nenghai Yu:
Exploring the Application of Large-scale Pre-trained Models on Adverse Weather Removal. CoRR abs/2306.09008 (2023) - [i101]Kai Liu, Sheng Jin, Zhihang Fu, Ze Chen, Rongxin Jiang, Jieping Ye:
Uncertainty-aware Unsupervised Multi-Object Tracking. CoRR abs/2307.15409 (2023) - [i100]Haomin Wen, Youfang Lin, Lixia Wu, Xiaowei Mao, Tianyue Cai, Yunfeng Hou, Shengnan Guo, Yuxuan Liang, Guangyin Jin, Yiji Zhao, Roger Zimmermann, Jieping Ye, Huaiyu Wan:
A Survey on Service Route and Time Prediction in Instant Delivery: Taxonomy, Progress, and Prospects. CoRR abs/2309.01194 (2023) - [i99]Zhihao Shi, Jie Wang, Fanghua Lu, Hanzhu Chen, Defu Lian, Zheng Wang, Jieping Ye, Feng Wu:
Label Deconvolution for Node Representation Learning on Large-scale Attributed Graphs against Learning Bias. CoRR abs/2309.14907 (2023) - [i98]Shaotian Yan, Chen Shen, Junjie Liu, Jieping Ye:
Concise and Organized Perception Facilitates Large Language Models for Deductive Reasoning. CoRR abs/2310.03309 (2023) - [i97]Lanyun Zhu, Tianrun Chen, Deyi Ji, Jieping Ye, Jun Liu:
LLaFS: When Large-Language Models Meet Few-Shot Segmentation. CoRR abs/2311.16926 (2023) - 2022
- [j124]Shupeng Gui, Xiangliang Zhang, Pan Zhong, Shuang Qiu, Mingrui Wu, Jieping Ye, Zhengdao Wang, Ji Liu:
PINE: Universal Deep Embedding for Graph Nodes via Partial Permutation Invariant Set Functions. IEEE Trans. Pattern Anal. Mach. Intell. 44(2): 770-782 (2022) - [j123]Yuan Cao, Junwei Liu, Heng Qi, Jie Gui, Keqiu Li, Jieping Ye, Chao Liu:
Scalable Distributed Hashing for Approximate Nearest Neighbor Search. IEEE Trans. Image Process. 31: 472-484 (2022) - [j122]Yiwen Sun, Kun Fu, Zheng Wang, Donghua Zhou, Kailun Wu, Jieping Ye, Changshui Zhang:
CoDriver ETA: Combine Driver Information in Estimated Time of Arrival by Driving Style Learning Auxiliary Task. IEEE Trans. Intell. Transp. Syst. 23(5): 4037-4048 (2022) - [j121]Siyuan Feng, Jintao Ke, Hai Yang, Jieping Ye:
A Multi-Task Matrix Factorized Graph Neural Network for Co-Prediction of Zone-Based and OD-Based Ride-Hailing Demand. IEEE Trans. Intell. Transp. Syst. 23(6): 5704-5716 (2022) - [j120]Yiwen Sun, Wenzheng Hu, Donghua Zhou, Baichuan Mo, Kun Fu, Zhengping Che, Zheng Wang, Shenhao Wang, Jinhua Zhao, Jieping Ye, Jian Tang, Changshui Zhang:
Alleviating Data Sparsity Problems in Estimated Time of Arrival via Auxiliary Metric Learning. IEEE Trans. Intell. Transp. Syst. 23(12): 23231-23243 (2022) - [j119]Guangtao Wang, Gao Cong, Ying Zhang, Zhen Hai, Jieping Ye:
A Synopsis Based Approach for Itemset Frequency Estimation over Massive Multi-Transaction Stream. ACM Trans. Knowl. Discov. Data 16(2): 29:1-29:30 (2022) - [j118]Liang Zhao, Yuyang Gao, Jieping Ye, Feng Chen, Yanfang Ye, Chang-Tien Lu, Naren Ramakrishnan:
Spatio-Temporal Event Forecasting Using Incremental Multi-Source Feature Learning. ACM Trans. Knowl. Discov. Data 16(2): 40:1-40:28 (2022) - [j117]Jintao Ke, Feng Xiao, Hai Yang, Jieping Ye:
Learning to Delay in Ride-Sourcing Systems: A Multi-Agent Deep Reinforcement Learning Framework. IEEE Trans. Knowl. Data Eng. 34(5): 2280-2292 (2022) - [j116]Xuanzhao Wang, Zhengping Che, Bo Jiang, Ning Xiao, Ke Yang, Jian Tang, Jieping Ye, Jingyu Wang, Qi Qi:
Robust Unsupervised Video Anomaly Detection by Multipath Frame Prediction. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2301-2312 (2022) - [c252]Zhe Jiang, Liang Zhao, Xun Zhou, Robert N. Stewart, Junbo Zhang, Shashi Shekhar, Jieping Ye:
DeepSpatial'22: The 3rd International Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems. KDD 2022: 4878-4879 - [c251]Chuishi Meng, Yanhua Li, Yu Zheng, Jieping Ye, Qiang Yang, Philip S. Yu, Ouri Wolfson:
The 11th International Workshop on Urban Computing. KDD 2022: 4886-4887 - [c250]Jian Zhang, Jian Tang, Yiran Chen, Jie Liu, Jieping Ye, Marilyn Wolf, Vijaykrishnan Narayanan, Mani B. Srivastava, Michael I. Jordan, Victor Bahl:
The 5th Artificial Intelligence of Things (AIoT) Workshop. KDD 2022: 4912-4913 - [c249]Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang:
In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle. SIGMOD Conference 2022: 1286-1300 - [c248]Zhanqiu Zhang, Jie Wang, Jieping Ye, Feng Wu:
Rethinking Graph Convolutional Networks in Knowledge Graph Completion. WWW 2022: 798-807 - [i96]Zhanqiu Zhang, Jie Wang, Jieping Ye, Feng Wu:
Rethinking Graph Convolutional Networks in Knowledge Graph Completion. CoRR abs/2202.05679 (2022) - [i95]Shikai Luo, Ying Yang, Chengchun Shi, Fang Yao, Jieping Ye, Hongtu Zhu:
Policy Evaluation for Temporal and/or Spatial Dependent Experiments in Ride-sourcing Platforms. CoRR abs/2202.10887 (2022) - [i94]Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang:
Stochastic Gradient Descent without Full Data Shuffle. CoRR abs/2206.05830 (2022) - [i93]Langzhang Liang, Zenglin Xu, Zixing Song, Irwin King, Jieping Ye:
ResNorm: Tackling Long-tailed Degree Distribution Issue in Graph Neural Networks via Normalization. CoRR abs/2206.08181 (2022) - [i92]Shuang Qiu, Xiaohan Wei, Jieping Ye, Zhaoran Wang, Zhuoran Yang:
Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions. CoRR abs/2207.12463 (2022) - 2021
- [j115]Shuang Qiu, Zhuoran Yang, Jieping Ye, Zhaoran Wang:
On Finite-Time Convergence of Actor-Critic Algorithm. IEEE J. Sel. Areas Inf. Theory 2(2): 652-664 (2021) - [j114]Jie Zhang, Qunxi Dong, Jie Shi, Qingyang Li, Cynthia M. Stonnington, Boris A. Gutman, Kewei Chen, Eric M. Reiman, Richard J. Caselli, Paul M. Thompson, Jieping Ye, Yalin Wang:
Predicting future cognitive decline with hyperbolic stochastic coding. Medical Image Anal. 70: 102009 (2021) - [j113]Wenjie Shang, Qingyang Li, Zhiwei (Tony) Qin, Yang Yu, Yiping Meng, Jieping Ye:
Partially observable environment estimation with uplift inference for reinforcement learning based recommendation. Mach. Learn. 110(9): 2603-2640 (2021) - [j112]Lina J. Karam, Jay Katupitiya, Vicente Milanés, Ioannis Pitas, Jieping Ye:
Autonomous Driving: Part 2-Learning and Cognition [From the Guest Editors]. IEEE Signal Process. Mag. 38(1): 20-21 (2021) - [j111]Huapeng Wu, Zhengxia Zou, Jie Gui, Wen-Jun Zeng, Jieping Ye, Jun Zhang, Hongyi Liu, Zhihui Wei:
Multi-Grained Attention Networks for Single Image Super-Resolution. IEEE Trans. Circuits Syst. Video Technol. 31(2): 512-522 (2021) - [j110]Zhiyuan Liu, Yang Liu, Cheng Lyu, Jieping Ye:
Building Personalized Transportation Model for Online Taxi-Hailing Demand Prediction. IEEE Trans. Cybern. 51(9): 4602-4610 (2021) - [j109]Zhengxia Zou, Tianyang Shi, Zhenwei Shi, Jieping Ye:
Adversarial Training for Solving Inverse Problems in Image Processing. IEEE Trans. Image Process. 30: 2513-2525 (2021) - [j108]Jie Gui, Yuan Cao, Heng Qi, Keqiu Li, Jieping Ye, Chao Liu, Xiaowei Xu:
Fast kNN Search in Weighted Hamming Space With Multiple Tables. IEEE Trans. Image Process. 30: 3985-3994 (2021) - [j107]Rui Han, Chi Harold Liu, Shilin Li, Lydia Y. Chen, Guoren Wang, Jian Tang, Jieping Ye:
SlimML: Removing Non-Critical Input Data in Large-Scale Iterative Machine Learning. IEEE Trans. Knowl. Data Eng. 33(5): 2223-2236 (2021) - [j106]Jie Zhang, Jianfeng Wu, Qingyang Li, Richard J. Caselli, Paul M. Thompson, Jieping Ye, Yalin Wang:
Multi-Resemblance Multi-Target Low-Rank Coding for Prediction of Cognitive Decline With Longitudinal Brain Images. IEEE Trans. Medical Imaging 40(8): 2030-2041 (2021) - [j105]Zhengtian Xu, Zhibin Chen, Yafeng Yin, Jieping Ye:
Equilibrium Analysis of Urban Traffic Networks with Ride-Sourcing Services. Transp. Sci. 55(6): 1260-1279 (2021) - [c247]Bingyu Liu, Yuhong Guo, Jieping Ye, Weihong Deng:
Selective Pseudo-Labeling with Reinforcement Learning for Semi-Supervised Domain Adaptation. BMVC 2021: 299 - [c246]Yiwen Sun, Yulu Wang, Kun Fu, Zheng Wang, Ziang Yan, Changshui Zhang, Jieping Ye:
FMA-ETA: Estimating Travel Time Entirely Based on FFN with Attention. ICASSP 2021: 3355-3359 - [c245]Fan Zhou, Chenfan Lu, Xiaocheng Tang, Fan Zhang, Zhiwei (Tony) Qin, Jieping Ye, Hongtu Zhu:
Multi-Objective Distributional Reinforcement Learning for Large-Scale Order Dispatching. ICDM 2021: 1541-1546 - [c244]Shuang Qiu, Xiaohan Wei, Jieping Ye, Zhaoran Wang, Zhuoran Yang:
Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions. ICML 2021: 8715-8725 - [c243]Shuang Qiu, Jieping Ye, Zhaoran Wang, Zhuoran Yang:
On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game. ICML 2021: 8737-8747 - [c242]Jun Chen, Jieping Ye, Fengyi Tang, Jiayu Zhou:
Automatic Detection of Alzheimer's Disease Using Spontaneous Speech Only. Interspeech 2021: 3830-3834 - [c241]Zhiwei (Tony) Qin, Hongtu Zhu, Jieping Ye:
Reinforcement Learning for Ridesharing: A Survey. ITSC 2021: 2447-2454 - [c240]Xiaocheng Tang, Fan Zhang, Zhiwei (Tony) Qin, Yansheng Wang, Dingyuan Shi, Bingchen Song, Yongxin Tong, Hongtu Zhu, Jieping Ye:
Value Function is All You Need: A Unified Learning Framework for Ride Hailing Platforms. KDD 2021: 3605-3615 - [c239]Jian Zhang, Jian Tang, Yiran Chen, Jie Liu, Jieping Ye, Marilyn Wolf, Vijaykrishnan Narayanan, Mani Srivastava, Michael I. Jordan, Victor Bahl:
The 4th Artificial Intelligence of Things (AIoT) Workshop. KDD 2021: 4179-4180 - [c238]Xun Zhou, Liang Zhao, Zhe Jiang, Robert N. Stewart, Shashi Shekhar, Jieping Ye:
DeepSpatial'21: 2nd International Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems. KDD 2021: 4183-4184 - [c237]Xiong-Hui Chen, Yang Yu, Qingyang Li, Fan-Ming Luo, Zhiwei (Tony) Qin, Wenjie Shang, Jieping Ye:
Offline Model-based Adaptable Policy Learning. NeurIPS 2021: 8432-8443 - [i91]Jie Zhang, Qunxi Dong, Jie Shi, Qingyang Li, Cynthia M. Stonnington, Boris A. Gutman, Kewei Chen, Eric M. Reiman, Richard J. Caselli, Paul M. Thompson, Jieping Ye, Yalin Wang:
Predicting Future Cognitive Decline with Hyperbolic Stochastic Coding. CoRR abs/2102.10503 (2021) - [i90]Yan Jiao, Xiaocheng Tang, Zhiwei (Tony) Qin, Shuaiji Li, Fan Zhang, Hongtu Zhu, Jieping Ye:
Real-world Ride-hailing Vehicle Repositioning using Deep Reinforcement Learning. CoRR abs/2103.04555 (2021) - [i89]Zhiwei (Tony) Qin, Hongtu Zhu, Jieping Ye:
Reinforcement Learning for Ridesharing: A Survey. CoRR abs/2105.01099 (2021) - [i88]Xiaocheng Tang, Fan Zhang, Zhiwei (Tony) Qin, Yansheng Wang, Dingyuan Shi, Bingchen Song, Yongxin Tong, Hongtu Zhu, Jieping Ye:
Value Function is All You Need: A Unified Learning Framework for Ride Hailing Platforms. CoRR abs/2105.08791 (2021) - [i87]Xiaocheng Tang, Zhiwei (Tony) Qin, Fan Zhang, Zhaodong Wang, Zhe Xu, Yintai Ma, Hongtu Zhu, Jieping Ye:
A Deep Value-network Based Approach for Multi-Driver Order Dispatching. CoRR abs/2106.04493 (2021) - [i86]Shuang Qiu, Jieping Ye, Zhaoran Wang, Zhuoran Yang:
On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game. CoRR abs/2110.09771 (2021) - 2020
- [j104]Zhiwei (Tony) Qin, Xiaocheng Tang, Yan Jiao, Fan Zhang, Zhe Xu, Hongtu Zhu, Jieping Ye:
Ride-Hailing Order Dispatching at DiDi via Reinforcement Learning. INFORMS J. Appl. Anal. 50(5): 272-286 (2020) - [j103]Lina J. Karam, Jay Katupitiya, Vicente Milanés, Ioannis Pitas, Jieping Ye:
Autonomous Driving: Part 1-Sensing and Perception [From the Guest Editors]. IEEE Signal Process. Mag. 37(4): 11-13 (2020) - [j102]Wenlu Zhang, Rongjian Li, Tao Zeng, Qian Sun, Sudhir Kumar, Jieping Ye, Shuiwang Ji:
Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis. IEEE Trans. Big Data 6(2): 322-333 (2020) - [j101]Yang Liu, Zhiyuan Liu, Cheng Lyu, Jieping Ye:
Attention-Based Deep Ensemble Net for Large-Scale Online Taxi-Hailing Demand Prediction. IEEE Trans. Intell. Transp. Syst. 21(11): 4798-4807 (2020) - [c236]Huiting Hong, Hantao Guo, Yucheng Lin, Xiaoqing Yang, Zang Li, Jieping Ye:
An Attention-Based Graph Neural Network for Heterogeneous Structural Learning. AAAI 2020: 4132-4139 - [c235]Ning Liu, Xiaolong Ma, Zhiyuan Xu, Yanzhi Wang, Jian Tang, Jieping Ye:
AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates. AAAI 2020: 4876-4883 - [c234]Peng Wang, Jiang Xu, Chunyi Liu, Hao Feng, Zang Li, Jieping Ye:
Masked-field Pre-training for User Intent Prediction. CIKM 2020: 2789-2796 - [c233]Guojun Wu, Yanhua Li, Shikai Luo, Ge Song, Qichao Wang, Jing He, Jieping Ye, Xiaohu Qie, Hongtu Zhu:
A Joint Inverse Reinforcement Learning and Deep Learning Model for Drivers' Behavioral Prediction. CIKM 2020: 2805-2812 - [c232]Xiehe Huang, Weihong Deng, Haifeng Shen, Xiubao Zhang, Jieping Ye:
PropagationNet: Propagate Points to Curve to Learn Structure Information. CVPR 2020: 7263-7272 - [c231]Zhengxia Zou, Sen Lei, Tianyang Shi, Zhenwei Shi, Jieping Ye:
Deep Adversarial Decomposition: A Unified Framework for Separating Superimposed Images. CVPR 2020: 12803-12813 - [c230]Zhen Zhao, Yuhong Guo, Haifeng Shen, Jieping Ye:
Adaptive Object Detection with Dual Multi-label Prediction. ECCV (28) 2020: 54-69 - [c229]Zhen Zhao, Yuhong Guo, Jieping Ye:
Bi-Dimensional Feature Alignment for Cross-Domain Object Detection. ECCV Workshops (1) 2020: 671-686 - [c228]Yucheng Lin, Huiting Hong, Xiaoqing Yang, Pinghua Gong, Zang Li, Jieping Ye:
AHINE: Adaptive Heterogeneous Information Network Embedding. ICKG 2020: 100-107 - [c227]Hongzhi Shi, Quanming Yao, Qi Guo, Yaguang Li, Lingyu Zhang, Jieping Ye, Yong Li, Yan Liu:
Predicting Origin-Destination Flow via Multi-Perspective Graph Convolutional Network. ICDE 2020: 1818-1821 - [c226]Yuan Zhao, Lyuwei Wang, Luanxuan Hou, Chunsheng Gan, Zhipeng Huang, Xu Hu, Haifeng Shen, Jieping Ye:
Real Time Object Detection for Traffic Based on Knowledge Distillation: 3rd Place Solution to Pair Competition. ICME Workshops 2020: 1-6 - [c225]Zehui Yu, Xiehe Huang, Xiubao Zhang, Haifeng Shen, Qun (Tracy) Li, Weihong Deng, Jian Tang, Yi Yang, Jieping Ye:
A Multi-Modal Approach for Driver Gaze Prediction to Remove Identity Bias. ICMI 2020: 768-776 - [c224]Mo Sun, Jian Li, Hui Feng, Wei Gou, Haifeng Shen, Jian Tang, Yi Yang, Jieping Ye:
Multi-modal Fusion Using Spatio-temporal and Static Features for Group Emotion Recognition. ICMI 2020: 835-840 - [c223]Yiwen Sun, Kun Fu, Zheng Wang, Changshui Zhang, Jieping Ye:
Road Network Metric Learning for Estimated Time of Arrival. ICPR 2020: 1820-1827 - [c222]Yiwen Sun, Yulu Wang, Kun Fu, Zheng Wang, Changshui Zhang, Jieping Ye:
Constructing Geographic and Long-term Temporal Graph for Traffic Forecasting. ICPR 2020: 3483-3490 - [c221]Teng Ye, Wei Ai, Lingyu Zhang, Ning Luo, Lulu Zhang, Jieping Ye, Qiaozhu Mei:
Predicting Individual Treatment Effects of Large-scale Team Competitions in a Ride-sharing Economy. KDD 2020: 2368-2377 - [c220]Huiting Hong, Yucheng Lin, Xiaoqing Yang, Zang Li, Kun Fu, Zheng Wang, Xiaohu Qie, Jieping Ye:
HetETA: Heterogeneous Information Network Embedding for Estimating Time of Arrival. KDD 2020: 2444-2454 - [c219]Wenjuan Luo, Han Zhang, Xiaodi Yang, Lin Bo, Xiaoqing Yang, Zang Li, Xiaohu Qie, Jieping Ye:
Dynamic Heterogeneous Graph Neural Network for Real-time Event Prediction. KDD 2020: 3213-3223 - [c218]Kun Fu, Fanlin Meng, Jieping Ye, Zheng Wang:
CompactETA: A Fast Inference System for Travel Time Prediction. KDD 2020: 3337-3345 - [c217]Che Liu, Junfeng Jiang, Chao Xiong, Yi Yang, Jieping Ye:
Towards Building an Intelligent Chatbot for Customer Service: Learning to Respond at the Appropriate Time. KDD 2020: 3377-3385 - [c216]Shuang Qiu, Xiaohan Wei, Zhuoran Yang, Jieping Ye, Zhaoran Wang:
Upper Confidence Primal-Dual Reinforcement Learning for CMDP with Adversarial Loss. NeurIPS 2020 - [c215]Zhiyuan Xu, Kun Wu, Zhengping Che, Jian Tang, Jieping Ye:
Knowledge Transfer in Multi-Task Deep Reinforcement Learning for Continuous Control. NeurIPS 2020 - [c214]Bo Long, Jieping Ye, Zang Li, Huiji Gao, Sandeep Kumar Jha:
Deep Natural Language Processing for Search and Recommendation. SIGIR 2020: 2461-2463 - [c213]Tanfang Chen, Weiwei Wang, Wenyang Wei, Xing Shi, Xiangang Li, Jieping Ye, Kevin Knight:
DiDi's Machine Translation System for WMT2020. WMT@EMNLP 2020: 105-112 - [c212]Mengyue Yang, Qingyang Li, Zhiwei (Tony) Qin, Jieping Ye:
Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation. WWW 2020: 292-302 - [i85]Jie Gui, Zhenan Sun, Yonggang Wen, Dacheng Tao, Jieping Ye:
A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications. CoRR abs/2001.06937 (2020) - [i84]Chengchun Shi, Xiaoyu Wang, Shikai Luo, Rui Song, Hongtu Zhu, Jieping Ye:
A Reinforcement Learning Framework for Time-Dependent Causal Effects Evaluation in A/B Testing. CoRR abs/2002.01711 (2020) - [i83]Shuang Qiu, Xiaohan Wei, Zhuoran Yang, Jieping Ye, Zhaoran Wang:
Upper Confidence Primal-Dual Optimization: Stochastically Constrained Markov Decision Processes with Adversarial Losses and Unknown Transitions. CoRR abs/2003.00660 (2020) - [i82]Luanxuan Hou, Jie Cao, Yuan Zhao, Haifeng Shen, Yiping Meng, Ran He, Jieping Ye:
Augmented Parallel-Pyramid Net for Attention Guided Pose-Estimation. CoRR abs/2003.07516 (2020) - [i81]Zhen Zhao, Yuhong Guo, Haifeng Shen, Jieping Ye:
Adaptive Object Detection with Dual Multi-Label Prediction. CoRR abs/2003.12943 (2020) - [i80]Zhenpeng Li, Zhen Zhao, Yuhong Guo, Haifeng Shen, Jieping Ye:
Mutual Learning Network for Multi-Source Domain Adaptation. CoRR abs/2003.12944 (2020) - [i79]Mengyue Yang, Qingyang Li, Zhiwei (Tony) Qin, Jieping Ye:
Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation. CoRR abs/2004.01136 (2020) - [i78]Yiwen Sun, Yulu Wang, Kun Fu, Zheng Wang, Changshui Zhang, Jieping Ye:
Constructing Geographic and Long-term Temporal Graph for Traffic Forecasting. CoRR abs/2004.10958 (2020) - [i77]Chao Xiong, Che Liu, Zijun Xu, Junfeng Jiang, Jieping Ye:
Sequential Sentence Matching Network for Multi-turn Response Selection in Retrieval-based Chatbots. CoRR abs/2005.07923 (2020) - [i76]Bingyu Liu, Zhen Zhao, Zhenpeng Li, Jianan Jiang, Yuhong Guo, Jieping Ye:
Feature Transformation Ensemble Model with Batch Spectral Regularization for Cross-Domain Few-Shot Classification. CoRR abs/2005.08463 (2020) - [i75]Yiwen Sun, Yulu Wang, Kun Fu, Zheng Wang, Changshui Zhang, Jieping Ye:
Fusion Recurrent Neural Network. CoRR abs/2006.04069 (2020) - [i74]Yiwen Sun, Yulu Wang, Kun Fu, Zheng Wang, Ziang Yan, Changshui Zhang, Jieping Ye:
FMA-ETA: Estimating Travel Time Entirely Based on FFN With Attention. CoRR abs/2006.04077 (2020) - [i73]Zhen Zhao, Bingyu Liu, Yuhong Guo, Jieping Ye:
Ensemble Model with Batch Spectral Regularization and Data Blending for Cross-Domain Few-Shot Learning with Unlabeled Data. CoRR abs/2006.04323 (2020) - [i72]Jianan Jiang, Zhenpeng Li, Yuhong Guo, Jieping Ye:
A Transductive Multi-Head Model for Cross-Domain Few-Shot Learning. CoRR abs/2006.11384 (2020) - [i71]Yiwen Sun, Kun Fu, Zheng Wang, Changshui Zhang, Jieping Ye:
Road Network Metric Learning for Estimated Time of Arrival. CoRR abs/2006.13477 (2020) - [i70]Xiehe Huang, Weihong Deng, Haifeng Shen, Xiubao Zhang, Jieping Ye:
PropagationNet: Propagate Points to Curve to Learn Structure Information. CoRR abs/2006.14308 (2020) - [i69]Teng Ye, Wei Ai, Lingyu Zhang, Ning Luo, Lulu Zhang, Jieping Ye, Qiaozhu Mei:
Predicting Individual Treatment Effects of Large-scale Team Competitions in a Ride-sharing Economy. CoRR abs/2008.07364 (2020) - [i68]Shuang Qiu, Zhuoran Yang, Xiaohan Wei, Jieping Ye, Zhaoran Wang:
Single-Timescale Stochastic Nonconvex-Concave Optimization for Smooth Nonlinear TD Learning. CoRR abs/2008.10103 (2020) - [i67]Jiang Lu, Pinghua Gong, Jieping Ye, Changshui Zhang:
Learning from Very Few Samples: A Survey. CoRR abs/2009.02653 (2020) - [i66]Yucheng Lin, Huiting Hong, Xiaoqing Yang, Xiaodi Yang, Pinghua Gong, Jieping Ye:
Meta Graph Attention on Heterogeneous Graph with Node-Edge Co-evolution. CoRR abs/2010.04554 (2020) - [i65]Zhiyuan Xu, Kun Wu, Zhengping Che, Jian Tang, Jieping Ye:
Knowledge Transfer in Multi-Task Deep Reinforcement Learning for Continuous Control. CoRR abs/2010.07494 (2020) - [i64]Tanfang Chen, Weiwei Wang, Wenyang Wei, Xing Shi, Xiangang Li, Jieping Ye, Kevin Knight:
DiDi's Machine Translation System for WMT2020. CoRR abs/2010.08185 (2020) - [i63]Xuanzhao Wang, Zhengping Che, Ke Yang, Bo Jiang, Jian Tang, Jieping Ye, Jingyu Wang, Qi Qi:
Robust Unsupervised Video Anomaly Detection by Multi-Path Frame Prediction. CoRR abs/2011.02763 (2020) - [i62]Jintao Ke, Siyuan Feng, Zheng Zhu, Hai Yang, Jieping Ye:
Joint predictions of multi-modal ride-hailing demands: a deep multi-task multigraph learning-based approach. CoRR abs/2011.05602 (2020) - [i61]Zhen Zhao, Yuhong Guo, Jieping Ye:
Bi-Dimensional Feature Alignment for Cross-Domain Object Detection. CoRR abs/2011.07205 (2020) - [i60]Zhenpeng Li, Jianan Jiang, Yuhong Guo, Tiantian Tang, Chengxiang Zhuo, Jieping Ye:
Domain Adaptation with Incomplete Target Domains. CoRR abs/2012.01606 (2020) - [i59]Bingyu Liu, Yuhong Guo, Jieping Ye, Weihong Deng:
Selective Pseudo-Labeling with Reinforcement Learning for Semi-Supervised Domain Adaptation. CoRR abs/2012.03438 (2020) - [i58]Wen-Jun Zeng, Jieping Ye:
Successive Projection for Solving Systems of Nonlinear Equations/Inequalities. CoRR abs/2012.07555 (2020)
2010 – 2019
- 2019
- [j100]Yan Li, Lu Wang, Jiayu Zhou, Jieping Ye:
Multi-task learning based survival analysis for multi-source block-wise missing data. Neurocomputing 364: 95-107 (2019) - [j99]Bin Hong, Weizhong Zhang, Wei Liu, Jieping Ye, Deng Cai, Xiaofei He, Jie Wang:
Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction. J. Mach. Learn. Res. 20: 121:1-121:39 (2019) - [j98]Jie Wang, Zhanqiu Zhang, Jieping Ye:
Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets. J. Mach. Learn. Res. 20: 163:1-163:42 (2019) - [j97]Milad Makkie, Xiang Li, Shannon Quinn, Binbin Lin, Jieping Ye, Geoffrey Mon, Tianming Liu:
A Distributed Computing Platform for fMRI Big Data Analytics. IEEE Trans. Big Data 5(2): 109-119 (2019) - [j96]Wei Zhang, Jinglei Lv, Xiang Li, Dajiang Zhu, Xi Jiang, Shu Zhang, Yu Zhao, Lei Guo, Jieping Ye, Dewen Hu, Tianming Liu:
Experimental Comparisons of Sparse Dictionary Learning and Independent Component Analysis for Brain Network Inference From fMRI Data. IEEE Trans. Biomed. Eng. 66(1): 289-299 (2019) - [j95]Kefei Liu, Jieping Ye, Yang Yang, Li Shen, Hui Jiang:
A Unified Model for Joint Normalization and Differential Gene Expression Detection in RNA-Seq Data. IEEE ACM Trans. Comput. Biol. Bioinform. 16(2): 442-454 (2019) - [j94]Jintao Ke, Hai Yang, Hongyu Zheng, Xiqun Chen, Yitian Jia, Pinghua Gong, Jieping Ye:
Hexagon-Based Convolutional Neural Network for Supply-Demand Forecasting of Ride-Sourcing Services. IEEE Trans. Intell. Transp. Syst. 20(11): 4160-4173 (2019) - [c211]Ji Zhao, Dan Peng, Chuhan Wu, Huan Chen, Meiyu Yu, Wanji Zheng, Li Ma, Hua Chai, Jieping Ye, Xiaohu Qie:
Incorporating Semantic Similarity with Geographic Correlation for Query-POI Relevance Learning. AAAI 2019: 1270-1277 - [c210]Xu Geng, Yaguang Li, Leye Wang, Lingyu Zhang, Qiang Yang, Jieping Ye, Yan Liu:
Spatiotemporal Multi-Graph Convolution Network for Ride-Hailing Demand Forecasting. AAAI 2019: 3656-3663 - [c209]Ming Lin, Shuang Qiu, Jieping Ye, Xiaomin Song, Qi Qian, Liang Sun, Shenghuo Zhu, Rong Jin:
Which Factorization Machine Modeling Is Better: A Theoretical Answer with Optimal Guarantee. AAAI 2019: 4312-4319 - [c208]Tao Huang, Yintai Ma, Zhiwei (Tony) Qin, Jianfeng Zheng, Henry X. Liu, Hongtu Zhu, Jieping Ye:
Origin-destination Flow Prediction with Vehicle Trajectory Data and Semi-supervised Recurrent Neural Network. IEEE BigData 2019: 1450-1459 - [c207]Lingyu Zhang, Tianshu Song, Yongxin Tong, Zimu Zhou, Dan Li, Wei Ai, Lulu Zhang, Guobin Wu, Yan Liu, Jieping Ye:
Recommendation-based Team Formation for On-demand Taxi-calling Platforms. CIKM 2019: 59-68 - [c206]Jiarui Jin, Ming Zhou, Weinan Zhang, Minne Li, Zilong Guo, Zhiwei (Tony) Qin, Yan Jiao, Xiaocheng Tang, Chenxi Wang, Jun Wang, Guobin Wu, Jieping Ye:
CoRide: Joint Order Dispatching and Fleet Management for Multi-Scale Ride-Hailing Platforms. CIKM 2019: 1983-1992 - [c205]Ming Zhou, Jiarui Jin, Weinan Zhang, Zhiwei (Tony) Qin, Yan Jiao, Chenxi Wang, Guobin Wu, Yong Yu, Jieping Ye:
Multi-Agent Reinforcement Learning for Order-dispatching via Order-Vehicle Distribution Matching. CIKM 2019: 2645-2653 - [c204]Weinan Zhang, Haiming Jin, Lingyu Zhang, Hongtu Zhu, Zhenhui Jessie Li, Jieping Ye:
CIKM 2019 Workshop on Artificial Intelligence in Transportation (AI in transportation). CIKM 2019: 2995-2996 - [c203]Zhengxia Zou, Wenyuan Li, Tianyang Shi, Zhenwei Shi, Jieping Ye:
Generative Adversarial Training for Weakly Supervised Cloud Matting. ICCV 2019: 201-210 - [c202]Max Guangyu Li, Bo Jiang, Zhengping Che, Xuefeng Shi, Mengyao Liu, Yiping Meng, Jieping Ye, Yan Liu:
DBUS: Human Driving Behavior Understanding System. ICCV Workshops 2019: 2436-2444 - [c201]Peng Cheng, Lei Chen, Jieping Ye:
Cooperation-Aware Task Assignment in Spatial Crowdsourcing. ICDE 2019: 1442-1453 - [c200]Haipeng Chen, Yan Jiao, Zhiwei (Tony) Qin, Xiaocheng Tang, Hao Li, Bo An, Hongtu Zhu, Jieping Ye:
InBEDE: Integrating Contextual Bandit with TD Learning for Joint Pricing and Dispatch of Ride-Hailing Platforms. ICDM 2019: 61-70 - [c199]John Holler, Risto Vuorio, Zhiwei (Tony) Qin, Xiaocheng Tang, Yan Jiao, Tiancheng Jin, Satinder Singh, Chenxi Wang, Jieping Ye:
Deep Reinforcement Learning for Multi-driver Vehicle Dispatching and Repositioning Problem. ICDM 2019: 1090-1095 - [c198]Qunxi Dong, Jie Zhang, Qingyang Li, Paul M. Thompson, Richard J. Caselli, Jieping Ye, Yalin Wang:
Multi-task Dictionary Learning Based on Convolutional Neural Networks for Longitudinal Clinical Score Predictions in Alzheimer's Disease. HBAI@IJCAI 2019: 21-35 - [c197]Pei Yang, Qi Tan, Jieping Ye, Hanghang Tong, Jingrui He:
Deep Multi-Task Learning with Adversarial-and-Cooperative Nets. IJCAI 2019: 4078-4084 - [c196]Jun Chen, Ji Zhu, Jieping Ye:
An Attention-Based Hybrid Network for Automatic Detection of Alzheimer's Disease from Narrative Speech. INTERSPEECH 2019: 4085-4089 - [c195]Wenjie Shang, Yang Yu, Qingyang Li, Zhiwei (Tony) Qin, Yiping Meng, Jieping Ye:
Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation. KDD 2019: 566-576 - [c194]Xiaocheng Tang, Zhiwei (Tony) Qin, Fan Zhang, Zhaodong Wang, Zhe Xu, Yintai Ma, Hongtu Zhu, Jieping Ye:
A Deep Value-network Based Approach for Multi-Driver Order Dispatching. KDD 2019: 1780-1790 - [c193]Chunyi Liu, Peng Wang, Jiang Xu, Zang Li, Jieping Ye:
Automatic Dialogue Summary Generation for Customer Service. KDD 2019: 1957-1965 - [c192]Jieping Ye:
Transportation: A Data Driven Approach. KDD 2019: 3183 - [c191]Zhiwei (Tony) Qin, Jian Tang, Jieping Ye:
Deep Reinforcement Learning with Applications in Transportation. KDD 2019: 3201-3202 - [c190]Fan Zhou, Tengfei Li, Haibo Zhou, Hongtu Zhu, Jieping Ye:
Graph-Based Semi-Supervised Learning with Non-ignorable Non-response. NeurIPS 2019: 7013-7023 - [c189]Minne Li, Zhiwei (Tony) Qin, Yan Jiao, Yaodong Yang, Jun Wang, Chenxi Wang, Guobin Wu, Jieping Ye:
Efficient Ridesharing Order Dispatching with Mean Field Multi-Agent Reinforcement Learning. WWW 2019: 983-994 - [i57]Ming Lin, Shuang Qiu, Jieping Ye, Xiaomin Song, Qi Qian, Liang Sun, Shenghuo Zhu, Rong Jin:
Which Factorization Machine Modeling is Better: A Theoretical Answer with Optimal Guarantee. CoRR abs/1901.11149 (2019) - [i56]Minne Li, Zhiwei (Tony) Qin, Yan Jiao, Yaodong Yang, Zhichen Gong, Jun Wang, Chenxi Wang, Guobin Wu, Jieping Ye:
Efficient Ridesharing Order Dispatching with Mean Field Multi-Agent Reinforcement Learning. CoRR abs/1901.11454 (2019) - [i55]Jintao Ke, Feng Xiao, Hai Yang, Jieping Ye:
Optimizing Online Matching for Ride-Sourcing Services with Multi-Agent Deep Reinforcement Learning. CoRR abs/1902.06228 (2019) - [i54]Ji Zhao, Meiyu Yu, Huan Chen, Boning Li, Lingyu Zhang, Qi Song, Li Ma, Hua Chai, Jieping Ye:
POI Semantic Model with a Deep Convolutional Structure. CoRR abs/1903.07279 (2019) - [i53]Zhengping Che, Max Guangyu Li, Tracy Li, Bo Jiang, Xuefeng Shi, Xinsheng Zhang, Ying Lu, Guobin Wu, Yan Liu, Jieping Ye:
D2-City: A Large-Scale Dashcam Video Dataset of Diverse Traffic Scenarios. CoRR abs/1904.01975 (2019) - [i52]Zhengxia Zou, Zhenwei Shi, Yuhong Guo, Jieping Ye:
Object Detection in 20 Years: A Survey. CoRR abs/1905.05055 (2019) - [i51]Zhenyu Shou, Xuan Di, Jieping Ye, Hongtu Zhu, Robert C. Hampshire:
Where to Find Next Passengers on E-hailing Platforms? - A Markov Decision Process Approach. CoRR abs/1905.09906 (2019) - [i50]Jiarui Jin, Ming Zhou, Weinan Zhang, Minne Li, Zilong Guo, Zhiwei (Tony) Qin, Yan Jiao, Xiaocheng Tang, Chenxi Wang, Jun Wang, Guobin Wu, Jieping Ye:
CoRide: Joint Order Dispatching and Fleet Management for Multi-Scale Ride-Hailing Platforms. CoRR abs/1905.11353 (2019) - [i49]Xu Geng, Xiyu Wu, Lingyu Zhang, Qiang Yang, Yan Liu, Jieping Ye:
Multi-Modal Graph Interaction for Multi-Graph Convolution Network in Urban Spatiotemporal Forecasting. CoRR abs/1905.11395 (2019) - [i48]Ning Liu, Xiaolong Ma, Zhiyuan Xu, Yanzhi Wang, Jian Tang, Jieping Ye:
AutoSlim: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates. CoRR abs/1907.03141 (2019) - [i47]Guojun Wu, Yanhua Li, Zhenming Liu, Jie Bao, Yu Zheng, Jieping Ye, Jun Luo:
Reward Advancement: Transforming Policy under Maximum Causal Entropy Principle. CoRR abs/1907.05390 (2019) - [i46]Wenjie Shang, Yang Yu, Qingyang Li, Zhiwei (Tony) Qin, Yiping Meng, Jieping Ye:
Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation. CoRR abs/1907.06584 (2019) - [i45]Yucheng Lin, Xiaoqing Yang, Zang Li, Jieping Ye:
AHINE: Adaptive Heterogeneous Information Network Embedding. CoRR abs/1909.01087 (2019) - [i44]Huapeng Wu, Zhengxia Zou, Jie Gui, Wen-Jun Zeng, Jieping Ye, Jun Zhang, Hongyi Liu, Zhihui Wei:
Multi-grained Attention Networks for Single Image Super-Resolution. CoRR abs/1909.11937 (2019) - [i43]Shupeng Gui, Xiangliang Zhang, Pan Zhong, Shuang Qiu, Mingrui Wu, Jieping Ye, Zhengdao Wang, Ji Liu:
PINE: Universal Deep Embedding for Graph Nodes via Partial Permutation Invariant Set Functions. CoRR abs/1909.12903 (2019) - [i42]Ming Zhou, Jiarui Jin, Weinan Zhang, Zhiwei (Tony) Qin, Yan Jiao, Chenxi Wang, Guobin Wu, Yong Yu, Jieping Ye:
Multi-Agent Reinforcement Learning for Order-dispatching via Order-Vehicle Distribution Matching. CoRR abs/1910.02591 (2019) - [i41]Jintao Ke, Xiaoran Qin, Hai Yang, Zhengfei Zheng, Zheng Zhu, Jieping Ye:
Predicting origin-destination ride-sourcing demand with a spatio-temporal encoder-decoder residual multi-graph convolutional network. CoRR abs/1910.09103 (2019) - [i40]Yang Liu, Fanyou Wu, Baosheng Yu, Zhiyuan Liu, Jieping Ye:
Building Effective Large-Scale Traffic State Prediction System: Traffic4cast Challenge Solution. CoRR abs/1911.05699 (2019) - [i39]John Holler, Risto Vuorio, Zhiwei (Tony) Qin, Xiaocheng Tang, Yan Jiao, Tiancheng Jin, Satinder Singh, Chenxi Wang, Jieping Ye:
Deep Reinforcement Learning for Multi-Driver Vehicle Dispatching and Repositioning Problem. CoRR abs/1911.11260 (2019) - [i38]Huiting Hong, Hantao Guo, Yucheng Lin, Xiaoqing Yang, Zang Li, Jieping Ye:
An Attention-based Graph Neural Network for Heterogeneous Structural Learning. CoRR abs/1912.10832 (2019) - 2018
- [j93]Shaogang Ren, Shuai Huang, Jieping Ye, Xiaoning Qian:
Safe Feature Screening for Generalized LASSO. IEEE Trans. Pattern Anal. Mach. Intell. 40(12): 2992-3006 (2018) - [j92]Libin Zheng, Lei Chen, Jieping Ye:
Order Dispatch in Price-aware Ridesharing. Proc. VLDB Endow. 11(8): 853-865 (2018) - [j91]Yongxin Tong, Yuxiang Zeng, Zimu Zhou, Lei Chen, Jieping Ye, Ke Xu:
A Unified Approach to Route Planning for Shared Mobility. Proc. VLDB Endow. 11(11): 1633-1646 (2018) - [j90]Bashar Haddad, Sen Yang, Lina J. Karam, Jieping Ye, Nital S. Patel, Martin W. Braun:
Multifeature, Sparse-Based Approach for Defects Detection and Classification in Semiconductor Units. IEEE Trans Autom. Sci. Eng. 15(1): 145-159 (2018) - [j89]Lu Lin, Jianxin Li, Feng Chen, Jieping Ye, Jinpeng Huai:
Road Traffic Speed Prediction: A Probabilistic Model Fusing Multi-Source Data. IEEE Trans. Knowl. Data Eng. 30(7): 1310-1323 (2018) - [j88]Weizhong Zhang, Tingjin Luo, Shuang Qiu, Jieping Ye, Deng Cai, Xiaofei He, Jie Wang:
Identifying Genetic Risk Factors for Alzheimer's Disease via Shared Tree-Guided Feature Learning Across Multiple Tasks. IEEE Trans. Knowl. Data Eng. 30(11): 2145-2156 (2018) - [c188]Huaxiu Yao, Fei Wu, Jintao Ke, Xianfeng Tang, Yitian Jia, Siyu Lu, Pinghua Gong, Jieping Ye, Zhenhui Li:
Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction. AAAI 2018: 2588-2595 - [c187]Tieliang Gong, Guangtao Wang, Jieping Ye, Zongben Xu, Ming Lin:
Margin Based PU Learning. AAAI 2018: 3037-3044 - [c186]Ishan Jindal, Zhiwei (Tony) Qin, Xue-wen Chen, Matthew S. Nokleby, Jieping Ye:
Optimizing Taxi Carpool Policies via Reinforcement Learning and Spatio-Temporal Mining. IEEE BigData 2018: 1417-1426 - [c185]Carl Yang, Chao Zhang, Xuewen Chen, Jieping Ye, Jiawei Han:
Did You Enjoy the Ride? Understanding Passenger Experience via Heterogeneous Network Embedding. ICDE 2018: 1392-1403 - [c184]Guojun Wu, Yanhua Li, Jie Bao, Yu Zheng, Jieping Ye, Jun Luo:
Human-Centric Urban Transit Evaluation and Planning. ICDM 2018: 547-556 - [c183]Zhaodong Wang, Zhiwei (Tony) Qin, Xiaocheng Tang, Jieping Ye, Hongtu Zhu:
Deep Reinforcement Learning with Knowledge Transfer for Online Rides Order Dispatching. ICDM 2018: 617-626 - [c182]Jie Zhang, Yanshuai Tu, Qingyang Li, Richard J. Caselli, Paul M. Thompson, Jieping Ye, Yalin Wang:
Multi-task sparse screening for predicting future clinical scores using longitudinal cortical thickness measures. ISBI 2018: 1406-1410 - [c181]Zheng Wang, Kun Fu, Jieping Ye:
Learning to Estimate the Travel Time. KDD 2018: 858-866 - [c180]Zhe Xu, Zhixin Li, Qingwen Guan, Dingshui Zhang, Qiang Li, Junxiao Nan, Chunyang Liu, Wei Bian, Jieping Ye:
Large-Scale Order Dispatch in On-Demand Ride-Hailing Platforms: A Learning and Planning Approach. KDD 2018: 905-913 - [c179]Yaguang Li, Kun Fu, Zheng Wang, Cyrus Shahabi, Jieping Ye, Yan Liu:
Multi-task Representation Learning for Travel Time Estimation. KDD 2018: 1695-1704 - [c178]Yan Li, Jieping Ye:
Learning Adversarial Networks for Semi-Supervised Text Classification via Policy Gradient. KDD 2018: 1715-1723 - [c177]Chen Luo, Zhengzhang Chen, Lu-An Tang, Anshumali Shrivastava, Zhichun Li, Haifeng Chen, Jieping Ye:
TINET: Learning Invariant Networks via Knowledge Transfer. KDD 2018: 1890-1899 - [c176]Zhiwei (Tony) Qin, Chengxiang Zhuo, Wei Tan, Jun Xie, Jieping Ye:
Large-Scale Targeted Marketing by Supervised PageRank with Seeds. MLDM (2) 2018: 409-424 - [c175]Yan Li, Tao Yang, Jiayu Zhou, Jieping Ye:
Multi-Task Learning based Survival Analysis for Predicting Alzheimer's Disease Progression with Multi-Source Block-wise Missing Data. SDM 2018: 288-296 - [c174]Lingyu Zhang, Wei Ai, Chuan Yuan, Yuhui Zhang, Jieping Ye:
Taxi or Hitchhiking: Predicting Passenger's Preferred Service on Ride Sharing Platforms. SIGIR 2018: 1041-1044 - [c173]Jieping Ye:
Big Data at Didi Chuxing. SIGIR 2018: 1341 - [c172]Yongxin Tong, Libin Wang, Zimu Zhou, Lei Chen, Bowen Du, Jieping Ye:
Dynamic Pricing in Spatial Crowdsourcing: A Matching-Based Approach. SIGMOD Conference 2018: 773-788 - [i37]Huaxiu Yao, Fei Wu, Jintao Ke, Xianfeng Tang, Yitian Jia, Siyu Lu, Pinghua Gong, Jieping Ye, Zhenhui Li:
Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction. CoRR abs/1802.08714 (2018) - [i36]Shupeng Gui, Xiangliang Zhang, Shuang Qiu, Mingrui Wu, Jieping Ye, Ji Liu:
GESF: A Universal Discriminative Mapping Mechanism for Graph Representation Learning. CoRR abs/1805.11182 (2018) - [i35]Ishan Jindal, Zhiwei (Tony) Qin, Xue-wen Chen, Matthew S. Nokleby, Jieping Ye:
Optimizing Taxi Carpool Policies via Reinforcement Learning and Spatio-Temporal Mining. CoRR abs/1811.04345 (2018) - 2017
- [j87]Jinglei Lv, Binbin Lin, Qingyang Li, Wei Zhang, Yu Zhao, Xi Jiang, Lei Guo, Junwei Han, Xintao Hu, Christine Cong Guo, Jieping Ye, Tianming Liu:
Task fMRI data analysis based on supervised stochastic coordinate coding. Medical Image Anal. 38: 1-16 (2017) - [j86]Yongxin Tong, Libin Wang, Zimu Zhou, Bolin Ding, Lei Chen, Jieping Ye, Ke Xu:
Flexible Online Task Assignment in Real-Time Spatial Data. Proc. VLDB Endow. 10(11): 1334-1345 (2017) - [j85]Liang Zhao, Qian Sun, Jieping Ye, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan:
Feature Constrained Multi-Task Learning Models for Spatiotemporal Event Forecasting. IEEE Trans. Knowl. Data Eng. 29(5): 1059-1072 (2017) - [c171]Dong Wang, Wei Cao, Jian Li, Jieping Ye:
DeepSD: Supply-Demand Prediction for Online Car-Hailing Services Using Deep Neural Networks. ICDE 2017: 243-254 - [c170]Lu Wang, Yan Li, Jiayu Zhou, Dongxiao Zhu, Jieping Ye:
Multi-task Survival Analysis. ICDM 2017: 485-494 - [c169]Guangtao Wang, Jiayu Zhou, Jingjie Ni, Tingjin Luo, Wei Long, Hai Zhen, Gao Cong, Jieping Ye:
Robust Self-Tuning Sparse Subspace Clustering. ICDM Workshops 2017: 858-865 - [c168]Weizhong Zhang, Bin Hong, Wei Liu, Jieping Ye, Deng Cai, Xiaofei He, Jie Wang:
Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction. ICML 2017: 4016-4025 - [c167]Jie Zhang, Qingyang Li, Richard J. Caselli, Paul M. Thompson, Jieping Ye, Yalin Wang:
Multi-source Multi-target Dictionary Learning for Prediction of Cognitive Decline. IPMI 2017: 184-197 - [c166]Yu Zhao, Xiang Li, Milad Makkie, Shannon Quinn, Binbin Lin, Jieping Ye, Tianming Liu:
Template-guided Functional Network Identification via Supervised Dictionary Learning. ISBI 2017: 72-76 - [c165]Jie Zhang, Yonghui Fan, Qingyang Li, Paul M. Thompson, Jieping Ye, Yalin Wang:
Empowering cortical thickness measures in clinical diagnosis of Alzheimer's disease with spherical sparse coding. ISBI 2017: 446-450 - [c164]Tingjin Luo, Weizhong Zhang, Shang Qiu, Yang Yang, Dongyun Yi, Guangtao Wang, Jieping Ye, Jie Wang:
Functional Annotation of Human Protein Coding Isoforms via Non-convex Multi-Instance Learning. KDD 2017: 345-354 - [c163]Kai Zhang, Chuanren Liu, Jie Zhang, Hui Xiong, Eric P. Xing, Jieping Ye:
Randomization or Condensation?: Linear-Cost Matrix Sketching Via Cascaded Compression Sampling. KDD 2017: 615-623 - [c162]Yongxin Tong, Yuqiang Chen, Zimu Zhou, Lei Chen, Jie Wang, Qiang Yang, Jieping Ye, Weifeng Lv:
The Simpler The Better: A Unified Approach to Predicting Original Taxi Demands based on Large-Scale Online Platforms. KDD 2017: 1653-1662 - [c161]Lingyu Zhang, Tao Hu, Yue Min, Guobin Wu, Junying Zhang, Pengcheng Feng, Pinghua Gong, Jieping Ye:
A Taxi Order Dispatch Model based On Combinatorial Optimization. KDD 2017: 2151-2159 - [c160]Xiang Li, Aoxiao Zhong, Ming Lin, Ning Guo, Mu Sun, Arkadiusz Sitek, Jieping Ye, James Thrall, Quanzheng Li:
Self-paced Convolutional Neural Network for Computer Aided Detection in Medical Imaging Analysis. MLMI@MICCAI 2017: 212-219 - [c159]Zhi Nie, Binbin Lin, Shuai Huang, Naren Ramakrishnan, Wei Fan, Jieping Ye:
Pruning Decision Trees via Max-Heap Projection. SDM 2017: 10-18 - [c158]Yashu Liu, Shuang Qiu, Ping Zhang, Pinghua Gong, Fei Wang, Guoliang Xue, Jieping Ye:
Computational Drug Discovery with Dyadic Positive-Unlabeled Learning. SDM 2017: 45-53 - [i34]Shuang Qiu, Tingjin Luo, Jieping Ye, Ming Lin:
Nonconvex One-bit Single-label Multi-label Learning. CoRR abs/1703.06104 (2017) - [i33]Qingyang Li, Dajiang Zhu, Jie Zhang, Derrek Paul Hibar, Neda Jahanshad, Yalin Wang, Jieping Ye, Paul M. Thompson, Jie Wang:
Large-scale Feature Selection of Risk Genetic Factors for Alzheimer's Disease via Distributed Group Lasso Regression. CoRR abs/1704.08383 (2017) - [i32]Hemanth Venkateswara, Prasanth Lade, Jieping Ye, Sethuraman Panchanathan:
Coupled Support Vector Machines for Supervised Domain Adaptation. CoRR abs/1706.07525 (2017) - [i31]Hemanth Venkateswara, Prasanth Lade, Binbin Lin, Jieping Ye, Sethuraman Panchanathan:
Efficient Approximate Solutions to Mutual Information Based Global Feature Selection. CoRR abs/1706.07535 (2017) - [i30]Xiang Li, Aoxiao Zhong, Ming Lin, Ning Guo, Mu Sun, Arkadiusz Sitek, Jieping Ye, James Thrall, Quanzheng Li:
Self-paced Convolutional Neural Network for Computer Aided Detection in Medical Imaging Analysis. CoRR abs/1707.06145 (2017) - [i29]Milad Makkie, Xiang Li, Binbin Lin, Jieping Ye, Mojtaba Sedigh Fazli, Tianming Liu, Shannon Quinn:
Distributed rank-1 dictionary learning: Towards fast and scalable solutions for fMRI big data analytics. CoRR abs/1708.02638 (2017) - [i28]Jie Zhang, Qingyang Li, Richard J. Caselli, Jieping Ye, Yalin Wang:
Multi-task Dictionary Learning based Convolutional Neural Network for Computer aided Diagnosis with Longitudinal Images. CoRR abs/1709.00042 (2017) - [i27]Tao Yang, Paul M. Thompson, Sihai Zhao, Jieping Ye:
Identifying Genetic Risk Factors via Sparse Group Lasso with Group Graph Structure. CoRR abs/1709.03645 (2017) - [i26]Ishan Jindal, Zhiwei (Tony) Qin, Xue-wen Chen, Matthew S. Nokleby, Jieping Ye:
A Unified Neural Network Approach for Estimating Travel Time and Distance for a Taxi Trip. CoRR abs/1710.04350 (2017) - 2016
- [j84]Kefei Liu, Lei Huang, Hing-Cheung So, Jieping Ye:
Multidimensional folding for sinusoidal order selection. Digit. Signal Process. 48: 349-360 (2016) - [j83]Kefei Liu, João Paulo C. L. da Costa, Hing-Cheung So, Lei Huang, Jieping Ye:
Detection of number of components in CANDECOMP/PARAFAC models via minimum description length. Digit. Signal Process. 51: 110-123 (2016) - [j82]Zhenfeng Zhu, Jian Cheng, Yao Zhao, Jieping Ye:
LSSLP - Local structure sensitive label propagation. Inf. Sci. 332: 19-32 (2016) - [j81]Lei Wang, Ce Zhu, Jieping Ye, Juergen Gall:
Guest Editors' Introduction: Special issue on deep learning with applications to visual representation and analysis. Signal Process. Image Commun. 47: 463-464 (2016) - [j80]Yashu Liu, Jie Wang, Jieping Ye:
An Efficient Algorithm For Weak Hierarchical Lasso. ACM Trans. Knowl. Discov. Data 10(3): 32:1-32:24 (2016) - [j79]Pei Yang, Hongxia Yang, Haoda Fu, Dawei Zhou, Jieping Ye, Theodoros Lappas, Jingrui He:
Jointly Modeling Label and Feature Heterogeneity in Medical Informatics. ACM Trans. Knowl. Discov. Data 10(4): 39:1-39:25 (2016) - [c157]Milad Makkie, Xiang Li, Tianming Liu, Shannon Quinn, Binbin Lin, Jieping Ye:
Distributed rank-1 dictionary learning: Towards fast and scalable solutions for fMRI big data analytics. IEEE BigData 2016: 3396-3403 - [c156]Yan Li, Lu Wang, Jie Wang, Jieping Ye, Chandan K. Reddy:
Transfer Learning for Survival Analysis via Efficient L2, 1-Norm Regularized Cox Regression. ICDM 2016: 231-240 - [c155]Bashar Haddad, Lina J. Karam, Jieping Ye, Nital Patel, Martin W. Braun:
Multi-feature sparse-based defect detection and classification in semiconductor units. ICIP 2016: 754-758 - [c154]Syed Abbas Zilqurnain Naqvi, Shandian Zhe, Yuan Qi, Yifan Yang, Jieping Ye:
Fast Laplace Approximation for Sparse Bayesian Spike and Slab Models. IJCAI 2016: 1867-1973 - [c153]Xiang Li, Binbin Lin, Jinglei Lv, Jieping Ye, Tianming Liu:
Modeling functional network dynamics via multi-scale dictionary learning and network continuums. ISBI 2016: 66-69 - [c152]Jie Zhang, Cynthia M. Stonnington, Qingyang Li, Jie Shi, Robert J. Bauer, Boris A. Gutman, Kewei Chen, Eric M. Reiman, Paul M. Thompson, Jieping Ye, Yalin Wang:
Applying sparse coding to surface multivariate tensor-based morphometry to predict future cognitive decline. ISBI 2016: 646-650 - [c151]Xiang Li, Milad Makkie, Binbin Lin, Mojtaba Sedigh Fazli, Ian Davidson, Jieping Ye, Tianming Liu, Shannon Quinn:
Scalable Fast Rank-1 Dictionary Learning for fMRI Big Data Analysis. KDD 2016: 511-519 - [c150]Kai Zhang, Shandian Zhe, Chaoran Cheng, Zhi Wei, Zhengzhang Chen, Haifeng Chen, Guofei Jiang, Yuan Qi, Jieping Ye:
Annealed Sparsity via Adaptive and Dynamic Shrinking. KDD 2016: 1325-1334 - [c149]Qingyang Li, Shuang Qiu, Shuiwang Ji, Paul M. Thompson, Jieping Ye, Jie Wang:
Parallel Lasso Screening for Big Data Optimization. KDD 2016: 1705-1714 - [c148]Yan Li, Jie Wang, Jieping Ye, Chandan K. Reddy:
A Multi-Task Learning Formulation for Survival Analysis. KDD 2016: 1715-1724 - [c147]Zhi Nie, Pinghua Gong, Jieping Ye:
Predict Risk of Relapse for Patients with Multiple Stages of Treatment of Depression. KDD 2016: 1795-1804 - [c146]Tao Yang, Jun Liu, Pinghua Gong, Ruiwen Zhang, Xiaotong Shen, Jieping Ye:
Absolute Fused Lasso and Its Application to Genome-Wide Association Studies. KDD 2016: 1955-1964 - [c145]Liang Zhao, Jieping Ye, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan:
Hierarchical Incomplete Multi-source Feature Learning for Spatiotemporal Event Forecasting. KDD 2016: 2085-2094 - [c144]Jie Zhang, Jie Shi, Cynthia M. Stonnington, Qingyang Li, Boris A. Gutman, Kewei Chen, Eric M. Reiman, Richard J. Caselli, Paul M. Thompson, Jieping Ye, Yalin Wang:
Hyperbolic Space Sparse Coding with Its Application on Prediction of Alzheimer's Disease in Mild Cognitive Impairment. MICCAI (1) 2016: 326-334 - [c143]Qingyang Li, Tao Yang, Liang Zhan, Derrek P. Hibar, Neda Jahanshad, Yalin Wang, Jieping Ye, Paul M. Thompson, Jie Wang:
Large-Scale Collaborative Imaging Genetics Studies of Risk Genetic Factors for Alzheimer's Disease Across Multiple Institutions. MICCAI (1) 2016: 335-343 - [c142]Dajiang Zhu, Binbin Lin, Joshua Faskowitz, Jieping Ye, Paul M. Thompson:
Embedded sparse representation of fMRI data via group-wise dictionary optimization. Image Processing 2016: 97841K - [c141]Ming Lin, Jieping Ye:
A Non-convex One-Pass Framework for Generalized Factorization Machine and Rank-One Matrix Sensing. NIPS 2016: 1633-1641 - [i25]Weizhong Zhang, Bin Hong, Jieping Ye, Deng Cai, Xiaofei He, Jie Wang:
Scaling Up Sparse Support Vector Machine by Simultaneous Feature and Sample Reduction. CoRR abs/1607.06996 (2016) - [i24]Kai Zhang, Chuanren Liu, Jie Zhang, Hui Xiong, Eric P. Xing, Jieping Ye:
Seeing the Forest from the Trees in Two Looks: Matrix Sketching by Cascaded Bilateral Sampling. CoRR abs/1607.07395 (2016) - [i23]Ming Lin, Jieping Ye:
A Non-convex One-Pass Framework for Generalized Factorization Machines and Rank-One Matrix Sensing. CoRR abs/1608.05995 (2016) - [i22]Qingyang Li, Tao Yang, Liang Zhan, Derrek P. Hibar, Neda Jahanshad, Yalin Wang, Jieping Ye, Paul M. Thompson, Jie Wang:
Large-scale Collaborative Imaging Genetics Studies of Risk Genetic Factors for Alzheimer's Disease Across Multiple Institutions. CoRR abs/1608.07251 (2016) - 2015
- [j78]Shuo Xiang, Xiaotong Shen, Jieping Ye:
Efficient nonconvex sparse group feature selection via continuous and discrete optimization. Artif. Intell. 224: 28-50 (2015) - [j77]Tao Zeng, Rongjian Li, Ravi Mukkamala, Jieping Ye, Shuiwang Ji:
Deep convolutional neural networks for annotating gene expression patterns in the mouse brain. BMC Bioinform. 16: 147:1-147:10 (2015) - [j76]Deepak Kadetotad, Zihan Xu, Abinash Mohanty, Pai-Yu Chen, Binbin Lin, Jieping Ye, Sarma B. K. Vrudhula, Shimeng Yu, Yu Cao, Jae-sun Seo:
Parallel Architecture With Resistive Crosspoint Array for Dictionary Learning Acceleration. IEEE J. Emerg. Sel. Topics Circuits Syst. 5(2): 194-204 (2015) - [j75]Qi Yan, Jieping Ye, Xiaotong Shen:
Simultaneous pursuit of sparseness and rank structures for matrix decomposition. J. Mach. Learn. Res. 16: 47-75 (2015) - [j74]Jie Wang, Peter Wonka, Jieping Ye:
Lasso screening rules via dual polytope projection. J. Mach. Learn. Res. 16: 1063-1101 (2015) - [j73]Jie Wang, Wei Fan, Jieping Ye:
Fused Lasso Screening Rules via the Monotonicity of Subdifferentials. IEEE Trans. Pattern Anal. Mach. Intell. 37(9): 1806-1820 (2015) - [j72]Shayok Chakraborty, Vineeth Nallure Balasubramanian, Qian Sun, Sethuraman Panchanathan, Jieping Ye:
Active Batch Selection via Convex Relaxations with Guaranteed Solution Bounds. IEEE Trans. Pattern Anal. Mach. Intell. 37(10): 1945-1958 (2015) - [j71]Sen Yang, Zhaosong Lu, Xiaotong Shen, Peter Wonka, Jieping Ye:
Fused Multiple Graphical Lasso. SIAM J. Optim. 25(2): 916-943 (2015) - [j70]Zheng Wang, Ming-Jun Lai, Zhaosong Lu, Wei Fan, Hasan Davulcu, Jieping Ye:
Orthogonal Rank-One Matrix Pursuit for Low Rank Matrix Completion. SIAM J. Sci. Comput. 37(1) (2015) - [j69]Jinglei Lv, Xi Jiang, Xiang Li, Dajiang Zhu, Shu Zhang, Shijie Zhao, Hanbo Chen, Tuo Zhang, Xintao Hu, Junwei Han, Jieping Ye, Lei Guo, Tianming Liu:
Holistic Atlases of Functional Networks and Interactions Reveal Reciprocal Organizational Architecture of Cortical Function. IEEE Trans. Biomed. Eng. 62(4): 1120-1131 (2015) - [j68]Zheng Wang, Jieping Ye:
Querying Discriminative and Representative Samples for Batch Mode Active Learning. ACM Trans. Knowl. Discov. Data 9(3): 17:1-17:23 (2015) - [j67]Buyue Qian, Xiang Wang, Jieping Ye, Ian Davidson:
A Reconstruction Error Based Framework for Multi-Label and Multi-View Learning. IEEE Trans. Knowl. Data Eng. 27(3): 594-607 (2015) - [j66]Moo K. Chung, Jamie L. Hanson, Jieping Ye, Richard J. Davidson, Seth D. Pollak:
Persistent Homology in Sparse Regression and Its Application to Brain Morphometry. IEEE Trans. Medical Imaging 34(9): 1928-1939 (2015) - [c140]Pai-Yu Chen, Deepak Kadetotad, Zihan Xu, Abinash Mohanty, Binbin Lin, Jieping Ye, Sarma B. K. Vrudhula, Jae-sun Seo, Yu Cao, Shimeng Yu:
Technology-design co-optimization of resistive cross-point array for accelerating learning algorithms on chip. DATE 2015: 854-859 - [c139]Pai-Yu Chen, Binbin Lin, I-Ting Wang, Tuo-Hung Hou, Jieping Ye, Sarma B. K. Vrudhula, Jae-sun Seo, Yu Cao, Shimeng Yu:
Mitigating Effects of Non-ideal Synaptic Device Characteristics for On-chip Learning. ICCAD 2015: 194-199 - [c138]Hemanth Venkateswara, Prasanth Lade, Binbin Lin, Jieping Ye, Sethuraman Panchanathan:
Efficient Approximate Solutions to Mutual Information Based Global Feature Selection. ICDM 2015: 1009-1014 - [c137]Pinghua Gong, Jieping Ye:
A Modified Orthant-Wise Limited Memory Quasi-Newton Method with Convergence Analysis. ICML 2015: 276-284 - [c136]Jie Wang, Jieping Ye:
Safe Screening for Multi-Task Feature Learning with Multiple Data Matrices. ICML 2015: 1747-1756 - [c135]Liang Zhan, Yashu Liu, Jiayu Zhou, Jieping Ye, Paul M. Thompson:
Boosting classification accuracy of diffusion MRI derived brain networks for the subtypes of mild cognitive impairment using higher order singular value decomposition. ISBI 2015: 131-135 - [c134]Tao Yang, Jie Wang, Qian Sun, Derrek P. Hibar, Neda Jahanshad, Li Liu, Yalin Wang, Liang Zhan, Paul M. Thompson, Jieping Ye:
Detecting genetic risk factors for Alzheimer's disease in whole genome sequence data via Lasso screening. ISBI 2015: 985-989 - [c133]Shayok Chakraborty, Vineeth Nallure Balasubramanian, Adepu Ravi Sankar, Sethuraman Panchanathan, Jieping Ye:
BatchRank: A Novel Batch Mode Active Learning Framework for Hierarchical Classification. KDD 2015: 99-108 - [c132]Chia-Tung Kuo, Xiang Wang, Peter B. Walker, Owen T. Carmichael, Jieping Ye, Ian Davidson:
Unified and Contrasting Cuts in Multiple Graphs: Application to Medical Imaging Segmentation. KDD 2015: 617-626 - [c131]Zheng Wang, Prithwish Chakraborty, Sumiko R. Mekaru, John S. Brownstein, Jieping Ye, Naren Ramakrishnan:
Dynamic Poisson Autoregression for Influenza-Like-Illness Case Count Prediction. KDD 2015: 1285-1294 - [c130]Sen Yang, Qian Sun, Shuiwang Ji, Peter Wonka, Ian Davidson, Jieping Ye:
Structural Graphical Lasso for Learning Mouse Brain Connectivity. KDD 2015: 1385-1394 - [c129]Wenlu Zhang, Rongjian Li, Tao Zeng, Qian Sun, Sudhir Kumar, Jieping Ye, Shuiwang Ji:
Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis. KDD 2015: 1475-1484 - [c128]Liang Zhao, Qian Sun, Jieping Ye, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan:
Multi-Task Learning for Spatio-Temporal Event Forecasting. KDD 2015: 1503-1512 - [c127]Qian Sun, Mohammad Shafkat Amin, Baoshi Yan, Craig Martell, Vita Markman, Anmol Bhasin, Jieping Ye:
Transfer Learning for Bilingual Content Classification. KDD 2015: 2147-2156 - [c126]Jinglei Lv, Binbin Lin, Wei Zhang, Xi Jiang, Xintao Hu, Junwei Han, Lei Guo, Jieping Ye, Tianming Liu:
Modeling Task FMRI Data via Supervised Stochastic Coordinate Coding. MICCAI (1) 2015: 239-246 - [c125]Hemanth Venkateswara, Prasanth Lade, Jieping Ye, Sethuraman Panchanathan:
Coupled Support Vector Machines for Supervised Domain Adaptation. ACM Multimedia 2015: 1295-1298 - [c124]Somak Aditya, Chitta Baral, Nguyen Ha Vo, Joohyung Lee, Jieping Ye, Zaw Naung, Barry Lumpkin, Jenny Hastings, Richard B. Scherl, Dawn M. Sweet, Daniela Inclezan:
Recognizing Social Constructs from Textual Conversation. HLT-NAACL 2015: 1293-1298 - [c123]Pinghua Gong, Jieping Ye:
HONOR: Hybrid Optimization for NOn-convex Regularized problems. NIPS 2015: 415-423 - [c122]Jie Wang, Jieping Ye:
Multi-Layer Feature Reduction for Tree Structured Group Lasso via Hierarchical Projection. NIPS 2015: 1279-1287 - [c121]Graciela Gonzalez, Chitta Baral, Jeff Kiefer, Suengchan Kim, Jieping Ye:
Session Introduction. Pacific Symposium on Biocomputing 2015: 80-83 - [c120]Tao Yang, Xinlin Zhao, Binbin Lin, Tao Zeng, Shuiwang Ji, Jieping Ye:
Automated Gene Expression Pattern Annotation in the Mouse Brain. Pacific Symposium on Biocomputing 2015: 144-155 - [c119]Zhi Nie, Tao Yang, Yashu Liu, Binbin Lin, Qingyang Li, Vaibhav A. Narayan, Gayle M. Wittenberg, Jieping Ye:
Melancholic Depression Prediction by Identifying Representative Features in Metabolic and Microarray Profiles with Missing Values. Pacific Symposium on Biocomputing 2015: 455-466 - [e3]Suresh Venkatasubramanian, Jieping Ye:
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30 - May 2, 2015. SIAM 2015, ISBN 978-1-61197-401-0 [contents] - [i21]Jie Wang, Jieping Ye:
Safe Screening for Multi-Task Feature Learning with Multiple Data Matrices. CoRR abs/1505.04073 (2015) - 2014
- [j65]Lei Yuan, Cheng Pan, Shuiwang Ji, Michael McCutchan, Zhi-Hua Zhou, Stuart J. Newfeld, Sudhir Kumar, Jieping Ye:
Automated annotation of developmental stages of Drosophila embryos in images containing spatial patterns of expression. Bioinform. 30(2): 266-273 (2014) - [j64]Ivan Montiel, Charlotte Konikoff, Bremen L. Braun, Mary Packard, L. Sian Gramates, Qian Sun, Jieping Ye, Sudhir Kumar:
myFX: a turn-key software for laboratory desktops to analyze spatial patterns of gene expression in Drosophila embryos. Bioinform. 30(9): 1319-1321 (2014) - [j63]Jianhui Chen, Jieping Ye:
Sparse trace norm regularization. Comput. Stat. 29(3): 623-639 (2014) - [j62]Rashmi Dubey, Jiayu Zhou, Yalin Wang, Paul M. Thompson, Jieping Ye:
Analysis of sampling techniques for imbalanced data: An n = 648 ADNI study. NeuroImage 87: 220-241 (2014) - [j61]Shuo Xiang, Lei Yuan, Wei Fan, Yalin Wang, Paul M. Thompson, Jieping Ye:
Bi-level multi-source learning for heterogeneous block-wise missing data. NeuroImage 102: 192-206 (2014) - [c118]Zihan Xu, Abinash Mohanty, Pai-Yu Chen, Deepak Kadetotad, Binbin Lin, Jieping Ye, Sarma B. K. Vrudhula, Shimeng Yu, Jae-sun Seo, Yu Cao:
Parallel Programming of Resistive Cross-point Array for Synaptic Plasticity. BICA 2014: 126-133 - [c117]Deepak Kadetotad, Zihan Xu, Abinash Mohanty, Pai-Yu Chen, Binbin Lin, Jieping Ye, Sarma B. K. Vrudhula, Shimeng Yu, Yu Cao, Jae-sun Seo:
Neurophysics-inspired parallel architecture with resistive crosspoint array for dictionary learning. BioCAS 2014: 536-539 - [c116]Qiang Zhang, Jiayu Zhou, Yilin Wang, Jieping Ye, Baoxin Li:
Image Cosegmentation via Multi-task Learning. BMVC 2014 - [c115]Zheng Wang, Ming-Jun Lai, Zhaosong Lu, Wei Fan, Hasan Davulcu, Jieping Ye:
Rank-One Matrix Pursuit for Matrix Completion. ICML 2014: 91-99 - [c114]Binbin Lin, Ji Yang, Xiaofei He, Jieping Ye:
Geodesic Distance Function Learning via Heat Flow on Vector Fields. ICML 2014: 145-153 - [c113]Jie Wang, Qingyang Li, Sen Yang, Wei Fan, Peter Wonka, Jieping Ye:
A Highly Scalable Parallel Algorithm for Isotropic Total Variation Models. ICML 2014: 235-243 - [c112]Jun Liu, Zheng Zhao, Jie Wang, Jieping Ye:
Safe Screening with Variational Inequalities and Its Application to Lasso. ICML 2014: 289-297 - [c111]Ji Liu, Jieping Ye, Ryohei Fujimaki:
Forward-Backward Greedy Algorithms for General Convex Smooth Functions over A Cardinality Constraint. ICML 2014: 503-511 - [c110]Jie Wang, Peter Wonka, Jieping Ye:
Scaling SVM and Least Absolute Deviations via Exact Data Reduction. ICML 2014: 523-531 - [c109]Jiayu Zhou, Fei Wang, Jianying Hu, Jieping Ye:
From micro to macro: data driven phenotyping by densification of longitudinal electronic medical records. KDD 2014: 135-144 - [c108]Yashu Liu, Jie Wang, Jieping Ye:
An efficient algorithm for weak hierarchical lasso. KDD 2014: 283-292 - [c107]Shuo Xiang, Tao Yang, Jieping Ye:
Simultaneous feature and feature group selection through hard thresholding. KDD 2014: 532-541 - [c106]Pinghua Gong, Jiayu Zhou, Wei Fan, Jieping Ye:
Efficient multi-task feature learning with calibration. KDD 2014: 761-770 - [c105]Sinchai Tsao, Niharika Gajawelli, Jiayu Zhou, Jie Shi, Jieping Ye, Yalin Wang, Natasha Leporé:
Evaluating the predictive power of multivariate tensor-based morphometry in Alzheimer's disease progression via convex fused sparse group Lasso. Image Processing 2014: 90342L - [c104]Jie Wang, Jiayu Zhou, Jun Liu, Peter Wonka, Jieping Ye:
A Safe Screening Rule for Sparse Logistic Regression. NIPS 2014: 1053-1061 - [c103]Jie Wang, Jieping Ye:
Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets. NIPS 2014: 2132-2140 - [c102]Graciela Gonzalez, Kevin Bretonnel Cohen, Robert Leaman, Casey S. Greene, Nigam Shah, Maricel G. Kann, Jieping Ye:
Session introduction. Pacific Symposium on Biocomputing 2014: 312-315 - [c101]Yashu Liu, Zhi Nie, Jiayu Zhou, Michael Farnum, Vaibhav A. Narayan, Gayle M. Wittenberg, Jieping Ye:
Sparse Generalized Functional Linear Model for Predicting Remission Status of Depression Patients. Pacific Symposium on Biocomputing 2014: 364-375 - [p1]Jianhui Chen, Jiayu Zhou, Jieping Ye:
Low-Rank and Sparse Multi-task Learning. Low-Rank and Sparse Modeling for Visual Analysis 2014: 151-180 - [i20]Chao Zhang, Lei Zhang, Wei Fan, Jieping Ye:
Generalization Bounds for Representative Domain Adaptation. CoRR abs/1401.0376 (2014) - [i19]Zheng Wang, Ming-Jun Lai, Zhaosong Lu, Wei Fan, Hasan Davulcu, Jieping Ye:
Orthogonal Rank-One Matrix Pursuit for Low Rank Matrix Completion. CoRR abs/1404.1377 (2014) - [i18]Binbin Lin, Ji Yang, Xiaofei He, Jieping Ye:
Geodesic Distance Function Learning via Heat Flow on Vector Fields. CoRR abs/1405.0133 (2014) - [i17]Pinghua Gong, Jieping Ye:
Linear Convergence of Variance-Reduced Projected Stochastic Gradient without Strong Convexity. CoRR abs/1406.1102 (2014) - [i16]Binbin Lin, Qingyang Li, Qian Sun, Ming-Jun Lai, Ian Davidson, Wei Fan, Jieping Ye:
Stochastic Coordinate Coding and Its Application for Drosophila Gene Expression Pattern Annotation. CoRR abs/1407.8147 (2014) - [i15]Moo K. Chung, Jamie L. Hanson, Jieping Ye, Richard J. Davidson, Seth D. Pollak:
Persistent Homology in Sparse Regression and Its Application to Brain Morphometry. CoRR abs/1409.0177 (2014) - [i14]Jie Wang, Jieping Ye:
Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets. CoRR abs/1410.4210 (2014) - 2013
- [j60]Qian Sun, Sherin Muckatira, Lei Yuan, Shuiwang Ji, Stuart J. Newfeld, Sudhir Kumar, Jieping Ye:
Image-level and group-level models for Drosophila gene expression pattern annotation. BMC Bioinform. 14: 350 (2013) - [j59]Pinghua Gong, Jieping Ye, Changshui Zhang:
Multi-stage multi-task feature learning. J. Mach. Learn. Res. 14(1): 2979-3010 (2013) - [j58]Yalin Wang, Lei Yuan, Jie Shi, Alexander Greve, Jieping Ye, Arthur W. Toga, Allan L. Reiss, Paul M. Thompson:
Applying tensor-based morphometry to parametric surfaces can improve MRI-based disease diagnosis. NeuroImage 74: 209-230 (2013) - [j57]Jiayu Zhou, Jun Liu, Vaibhav A. Narayan, Jieping Ye:
Modeling disease progression via multi-task learning. NeuroImage 78: 233-248 (2013) - [j56]Ji Liu, Przemyslaw Musialski, Peter Wonka, Jieping Ye:
Tensor Completion for Estimating Missing Values in Visual Data. IEEE Trans. Pattern Anal. Mach. Intell. 35(1): 208-220 (2013) - [j55]Jianhui Chen, Lei Tang, Jun Liu, Jieping Ye:
A Convex Formulation for Learning a Shared Predictive Structure from Multiple Tasks. IEEE Trans. Pattern Anal. Mach. Intell. 35(5): 1025-1038 (2013) - [j54]Shuai Huang, Jing Li, Jieping Ye, Adam Fleisher, Kewei Chen, Teresa Wu, Eric Reiman:
A Sparse Structure Learning Algorithm for Gaussian Bayesian Network Identification from High-Dimensional Data. IEEE Trans. Pattern Anal. Mach. Intell. 35(6): 1328-1342 (2013) - [j53]Lei Yuan, Jun Liu, Jieping Ye:
Efficient Methods for Overlapping Group Lasso. IEEE Trans. Pattern Anal. Mach. Intell. 35(9): 2104-2116 (2013) - [j52]Yao Hu, Debing Zhang, Jieping Ye, Xuelong Li, Xiaofei He:
Fast and Accurate Matrix Completion via Truncated Nuclear Norm Regularization. IEEE Trans. Pattern Anal. Mach. Intell. 35(9): 2117-2130 (2013) - [j51]Rita Chattopadhyay, Zheng Wang, Wei Fan, Ian Davidson, Sethuraman Panchanathan, Jieping Ye:
Batch Mode Active Sampling Based on Marginal Probability Distribution Matching. ACM Trans. Knowl. Discov. Data 7(3): 13:1-13:25 (2013) - [j50]Zheng Zhao, Lei Wang, Huan Liu, Jieping Ye:
On Similarity Preserving Feature Selection. IEEE Trans. Knowl. Data Eng. 25(3): 619-632 (2013) - [j49]Przemyslaw Musialski, Ming Cui, Jieping Ye, Anshuman Razdan, Peter Wonka:
A framework for interactive image color editing. Vis. Comput. 29(11): 1173-1186 (2013) - [c100]Shayok Chakraborty, Jiayu Zhou, Vineeth Nallure Balasubramanian, Sethuraman Panchanathan, Ian Davidson, Jieping Ye:
Active Matrix Completion. ICDM 2013: 81-90 - [c99]Pinghua Gong, Changshui Zhang, Zhaosong Lu, Jianhua Huang, Jieping Ye:
A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems. ICML (2) 2013: 37-45 - [c98]Ji Liu, Lei Yuan, Jieping Ye:
Guaranteed Sparse Recovery under Linear Transformation. ICML (3) 2013: 91-99 - [c97]Rita Chattopadhyay, Wei Fan, Ian Davidson, Sethuraman Panchanathan, Jieping Ye:
Joint Transfer and Batch-mode Active Learning. ICML (3) 2013: 253-261 - [c96]Shuo Xiang, Xiaoshen Tong, Jieping Ye:
Efficient Sparse Group Feature Selection via Nonconvex Optimization. ICML (1) 2013: 284-292 - [c95]Buyue Qian, Xiang Wang, Fei Wang, Hongfei Li, Jieping Ye, Ian Davidson:
Active Learning from Relative Queries. IJCAI 2013: 1614-1620 - [c94]Zheng Wang, Jieping Ye:
Querying discriminative and representative samples for batch mode active learning. KDD 2013: 158-166 - [c93]Shuo Xiang, Lei Yuan, Wei Fan, Yalin Wang, Paul M. Thompson, Jieping Ye:
Multi-source learning with block-wise missing data for Alzheimer's disease prediction. KDD 2013: 185-193 - [c92]Qian Sun, Shuo Xiang, Jieping Ye:
Robust principal component analysis via capped norms. KDD 2013: 311-319 - [c91]Sen Yang, Jie Wang, Wei Fan, Xiatian Zhang, Peter Wonka, Jieping Ye:
An efficient ADMM algorithm for multidimensional anisotropic total variation regularization problems. KDD 2013: 641-649 - [c90]Jiayu Zhou, Zhaosong Lu, Jimeng Sun, Lei Yuan, Fei Wang, Jieping Ye:
FeaFiner: biomarker identification from medical data through feature generalization and selection. KDD 2013: 1034-1042 - [c89]Jie Wang, Jiayu Zhou, Peter Wonka, Jieping Ye:
Lasso Screening Rules via Dual Polytope Projection. NIPS 2013: 1070-1078 - [c88]Graciela Gonzalez, Kevin Bretonnel Cohen, Casey S. Greene, Udo Hahn, Maricel G. Kann, Robert Leaman, Nigam Shah, Jieping Ye:
Session introduction. Pacific Symposium on Biocomputing 2013: 368-372 - [c87]Jianying Hu, Yashu Liu, Jimeng Sun, Jieping Ye, Jiayu Zhou:
Patient Risk Prediction Model via Top-k Stability Selection. SDM 2013: 55-63 - [c86]Ian Davidson, Buyue Qian, Xiang Wang, Jieping Ye:
Multi-objective Multi-view Spectral Clustering via Pareto Optimization. SDM 2013: 234-242 - [i13]Pinghua Gong, Changshui Zhang, Zhaosong Lu, Jianhua Huang, Jieping Ye:
A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems. CoRR abs/1303.4434 (2013) - [i12]Chao Zhang, Lei Zhang, Jieping Ye:
Generalization Bounds for Domain Adaptation. CoRR abs/1304.1574 (2013) - [i11]Jie Wang, Jiayu Zhou, Jun Liu, Peter Wonka, Jieping Ye:
A Safe Screening Rule for Sparse Logistic Regression. CoRR abs/1307.4145 (2013) - [i10]Jie Wang, Jun Liu, Jieping Ye:
Efficient Mixed-Norm Regularization: Algorithms and Safe Screening Methods. CoRR abs/1307.4156 (2013) - [i9]Jun Liu, Zheng Zhao, Jie Wang, Jieping Ye:
Safe Screening With Variational Inequalities and Its Applicaiton to LASSO. CoRR abs/1307.7577 (2013) - [i8]Jie Wang, Peter Wonka, Jieping Ye:
Scaling SVM and Least Absolute Deviations via Exact Data Reduction. CoRR abs/1310.7048 (2013) - 2012
- [j48]Sudhir Kumar, Kelly Boccia, Michael McCutchan, Jieping Ye:
Exploring spatial patterns of gene expression from Fruit Fly embryogenesis on the iPhone. Bioinform. 28(21): 2847-2848 (2012) - [j47]Lei Yuan, Alexander Woodard, Shuiwang Ji, Yuan Jiang, Zhi-Hua Zhou, Sudhir Kumar, Jieping Ye:
Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval. BMC Bioinform. 13: 107 (2012) - [j46]Ji Liu, Peter Wonka, Jieping Ye:
A Multi-Stage Framework for Dantzig Selector and LASSO. J. Mach. Learn. Res. 13: 1189-1219 (2012) - [j45]Lei Yuan, Yalin Wang, Paul M. Thompson, Vaibhav A. Narayan, Jieping Ye:
Multi-source feature learning for joint analysis of incomplete multiple heterogeneous neuroimaging data. NeuroImage 61(3): 622-632 (2012) - [j44]Ji Liu, Jun Liu, Peter Wonka, Jieping Ye:
Sparse non-negative tensor factorization using columnwise coordinate descent. Pattern Recognit. 45(1): 649-656 (2012) - [j43]Jieping Ye, Jun Liu:
Sparse methods for biomedical data. SIGKDD Explor. 14(1): 4-15 (2012) - [j42]Rita Chattopadhyay, Mark Jesunathadas, Brach Poston, Marco Santello, Jieping Ye, Sethuraman Panchanathan:
A Subject-Independent Method for Automatically Grading Electromyographic Features During a Fatiguing Contraction. IEEE Trans. Biomed. Eng. 59(6): 1749-1757 (2012) - [j41]Ying-Xin Li, Shuiwang Ji, Sudhir Kumar, Jieping Ye, Zhi-Hua Zhou:
Drosophila Gene Expression Pattern Annotation through Multi-Instance Multi-Label Learning. IEEE ACM Trans. Comput. Biol. Bioinform. 9(1): 98-112 (2012) - [j40]Jianhui Chen, Ji Liu, Jieping Ye:
Learning Incoherent Sparse and Low-Rank Patterns from Multiple Tasks. ACM Trans. Knowl. Discov. Data 5(4): 22:1-22:31 (2012) - [j39]Rita Chattopadhyay, Qian Sun, Wei Fan, Ian Davidson, Sethuraman Panchanathan, Jieping Ye:
Multisource domain adaptation and its application to early detection of fatigue. ACM Trans. Knowl. Discov. Data 6(4): 18:1-18:26 (2012) - [c85]Sukru Tikves, Sedat Gokalp, M'hamed H. Temkit, Sujogya Banerjee, Jieping Ye, Hasan Davulcu:
Perspective Analysis for Online Debates. ASONAM 2012: 898-905 - [c84]Debing Zhang, Yao Hu, Jieping Ye, Xuelong Li, Xiaofei He:
Matrix completion by Truncated Nuclear Norm Regularization. CVPR 2012: 2192-2199 - [c83]Yao Hu, Debing Zhang, Jun Liu, Jieping Ye, Xiaofei He:
Accelerated singular value thresholding for matrix completion. KDD 2012: 298-306 - [c82]Shuo Xiang, Yunzhang Zhu, Xiaotong Shen, Jieping Ye:
Optimal exact least squares rank minimization. KDD 2012: 480-488 - [c81]Rita Chattopadhyay, Zheng Wang, Wei Fan, Ian Davidson, Sethuraman Panchanathan, Jieping Ye:
Batch mode active sampling based on marginal probability distribution matching. KDD 2012: 741-749 - [c80]Pinghua Gong, Jieping Ye, Changshui Zhang:
Robust multi-task feature learning. KDD 2012: 895-903 - [c79]Sen Yang, Lei Yuan, Ying-Cheng Lai, Xiaotong Shen, Peter Wonka, Jieping Ye:
Feature grouping and selection over an undirected graph. KDD 2012: 922-930 - [c78]Jiayu Zhou, Jun Liu, Vaibhav A. Narayan, Jieping Ye:
Modeling disease progression via fused sparse group lasso. KDD 2012: 1095-1103 - [c77]Lei Yuan, Yalin Wang, Paul M. Thompson, Vaibhav A. Narayan, Jieping Ye:
Multi-source learning for joint analysis of incomplete multi-modality neuroimaging data. KDD 2012: 1149-1157 - [c76]Binbin Lin, Sen Yang, Chiyuan Zhang, Jieping Ye, Xiaofei He:
Multi-task Vector Field Learning. NIPS 2012: 296-304 - [c75]Pinghua Gong, Jieping Ye, Changshui Zhang:
Multi-Stage Multi-Task Feature Learning. NIPS 2012: 1997-2005 - [c74]Chao Zhang, Lei Zhang, Jieping Ye:
Generalization Bounds for Domain Adaptation. NIPS 2012 - [i7]Jun Liu, Shuiwang Ji, Jieping Ye:
Multi-Task Feature Learning Via Efficient l2,1-Norm Minimization. CoRR abs/1205.2631 (2012) - [i6]Shuo Xiang, Xiaotong Shen, Jieping Ye:
Efficient Sparse Group Feature Selection via Nonconvex Optimization. CoRR abs/1205.5075 (2012) - [i5]Jianhui Chen, Jieping Ye:
Sparse Trace Norm Regularization. CoRR abs/1206.0333 (2012) - [i4]Sen Yang, Zhisong Pan, Xiaotong Shen, Peter Wonka, Jieping Ye:
Fused Multiple Graphical Lasso. CoRR abs/1209.2139 (2012) - [i3]Jie Wang, Peter Wonka, Jieping Ye:
Lasso Screening Rules via Dual Polytope Projection. CoRR abs/1211.3966 (2012) - 2011
- [j38]Sudhir Kumar, Charlotte Konikoff, Bernard Van Emden, Christopher Busick, Kailah T. Davis, Shuiwang Ji, Lin-Wei Wu, Hector Ramos, Thomas Brody, Sethuraman Panchanathan, Jieping Ye, Timothy L. Karr, Kristyn Gerold, Michael McCutchan, Stuart J. Newfeld:
FlyExpress: visual mining of spatiotemporal patterns for genes and publications in Drosophila embryogenesis. Bioinform. 27(23): 3319-3320 (2011) - [j37]Jieping Ye, Teresa Wu, Jing Li, Kewei Chen:
Machine Learning Approaches for the Neuroimaging Study of Alzheimer's Disease. Computer 44(4): 99-101 (2011) - [j36]Shipeng Yu, Jinbo Bi, Jieping Ye:
Matrix-variate and higher-order probabilistic projections. Data Min. Knowl. Discov. 22(3): 372-392 (2011) - [j35]Xichuan Zhou, Hai-bin Shen, Jieping Ye:
Integrating outlier filtering in large margin training. J. Zhejiang Univ. Sci. C 12(5): 362-370 (2011) - [j34]Liang Sun, Shuiwang Ji, Jieping Ye:
Canonical Correlation Analysis for Multilabel Classification: A Least-Squares Formulation, Extensions, and Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 33(1): 194-200 (2011) - [j33]Xichuan Zhou, Jieping Ye, Yujie Feng:
Tuberculosis Surveillance by Analyzing Google Trends. IEEE Trans. Biomed. Eng. 58(8): 2247-2254 (2011) - [j32]Haiqin Yang, Zenglin Xu, Jieping Ye, Irwin King, Michael R. Lyu:
Efficient Sparse Generalized Multiple Kernel Learning. IEEE Trans. Neural Networks 22(3): 433-446 (2011) - [c73]Rita Chattopadhyay, Jieping Ye, Sethuraman Panchanathan:
Transfer Learning Framework for Early Detection of Fatigue Using Non-invasive Surface Electromyogram Signals (SEMG). AAAI Spring Symposium: Computational Physiology 2011 - [c72]Jianhui Chen, Jiayu Zhou, Jieping Ye:
Integrating low-rank and group-sparse structures for robust multi-task learning. KDD 2011: 42-50 - [c71]Rita Chattopadhyay, Jieping Ye, Sethuraman Panchanathan, Wei Fan, Ian Davidson:
Multi-source domain adaptation and its application to early detection of fatigue. KDD 2011: 717-725 - [c70]Jiayu Zhou, Lei Yuan, Jun Liu, Jieping Ye:
A multi-task learning formulation for predicting disease progression. KDD 2011: 814-822 - [c69]Shuai Huang, Jing Li, Jieping Ye, Adam Fleisher, Kewei Chen, Teresa Wu, Eric Reiman:
Brain effective connectivity modeling for alzheimer's disease by sparse gaussian bayesian network. KDD 2011: 931-939 - [c68]Lei Yuan, Jun Liu, Jieping Ye:
Efficient Methods for Overlapping Group Lasso. NIPS 2011: 352-360 - [c67]Jun Liu, Liang Sun, Jieping Ye:
Projection onto A Nonnegative Max-Heap. NIPS 2011: 487-495 - [c66]Qian Sun, Rita Chattopadhyay, Sethuraman Panchanathan, Jieping Ye:
A Two-Stage Weighting Framework for Multi-Source Domain Adaptation. NIPS 2011: 505-513 - [c65]Jiayu Zhou, Jianhui Chen, Jieping Ye:
Clustered Multi-Task Learning Via Alternating Structure Optimization. NIPS 2011: 702-710 - [c64]Shuai Huang, Jing Li, Jieping Ye, Teresa Wu, Kewei Chen, Adam Fleisher, Eric Reiman:
Identifying Alzheimer's Disease-Related Brain Regions from Multi-Modality Neuroimaging Data using Sparse Composite Linear Discrimination Analysis. NIPS 2011: 1431-1439 - 2010
- [j31]Ivaylo Ilinkin, Jieping Ye, Ravi Janardan:
Multiple structure alignment and consensus identification for proteins. BMC Bioinform. 11: 71 (2010) - [j30]Shuai Huang, Jing Li, Liang Sun, Jieping Ye, Adam Fleisher, Teresa Wu, Kewei Chen, Eric Reiman:
Learning brain connectivity of Alzheimer's disease by sparse inverse covariance estimation. NeuroImage 50(3): 935-949 (2010) - [j29]Ting Kei Pong, Paul Tseng, Shuiwang Ji, Jieping Ye:
Trace Norm Regularization: Reformulations, Algorithms, and Multi-Task Learning. SIAM J. Optim. 20(6): 3465-3489 (2010) - [j28]Shuiwang Ji, Lei Tang, Shipeng Yu, Jieping Ye:
A shared-subspace learning framework for multi-label classification. ACM Trans. Knowl. Discov. Data 4(2): 8:1-8:29 (2010) - [c63]Vineeth Nallure Balasubramanian, Shayok Chakraborty, Sethuraman Panchanathan, Jieping Ye:
Kernel Learning for Efficiency Maximization in the Conformal Predictions Framework. ICMLA 2010: 235-242 - [c62]Liang Sun, Betul Ceran, Jieping Ye:
A scalable two-stage approach for a class of dimensionality reduction techniques. KDD 2010: 313-322 - [c61]Jun Liu, Lei Yuan, Jieping Ye:
An efficient algorithm for a class of fused lasso problems. KDD 2010: 323-332 - [c60]Jianhui Chen, Ji Liu, Jieping Ye:
Learning incoherent sparse and low-rank patterns from multiple tasks. KDD 2010: 1179-1188 - [c59]Ji Liu, Peter Wonka, Jieping Ye:
Multi-Stage Dantzig Selector. NIPS 2010: 1450-1458 - [c58]Jun Liu, Jieping Ye:
Moreau-Yosida Regularization for Grouped Tree Structure Learning. NIPS 2010: 1459-1467 - [i2]Jun Liu, Jieping Ye:
Fast Overlapping Group Lasso. CoRR abs/1009.0306 (2010) - [i1]Jun Liu, Jieping Ye:
Efficient L1/Lq Norm Regularization. CoRR abs/1009.4766 (2010)
2000 – 2009
- 2009
- [j27]Shuiwang Ji, Ying-Xin Li, Zhi-Hua Zhou, Sudhir Kumar, Jieping Ye:
A bag-of-words approach for Drosophila gene expression pattern annotation. BMC Bioinform. 10 (2009) - [j26]Mingrui Wu, Jieping Ye:
A Small Sphere and Large Margin Approach for Novelty Detection Using Training Data with Outliers. IEEE Trans. Pattern Anal. Mach. Intell. 31(11): 2088-2092 (2009) - [j25]Saif Ali, Jieping Ye, Anshuman Razdan, Peter Wonka:
Compressed Facade Displacement Maps. IEEE Trans. Vis. Comput. Graph. 15(2): 262-273 (2009) - [c57]Ji Liu, Przemyslaw Musialski, Peter Wonka, Jieping Ye:
Tensor completion for estimating missing values in visual data. ICCV 2009: 2114-2121 - [c56]Jianhui Chen, Lei Tang, Jun Liu, Jieping Ye:
A convex formulation for learning shared structures from multiple tasks. ICML 2009: 137-144 - [c55]Shuiwang Ji, Jieping Ye:
An accelerated gradient method for trace norm minimization. ICML 2009: 457-464 - [c54]Jun Liu, Jieping Ye:
Efficient Euclidean projections in linear time. ICML 2009: 657-664 - [c53]Liang Sun, Shuiwang Ji, Jieping Ye:
A least squares formulation for a class of generalized eigenvalue problems in machine learning. ICML 2009: 977-984 - [c52]Zenglin Xu, Rong Jin, Jieping Ye, Michael R. Lyu, Irwin King:
Non-monotonic feature selection. ICML 2009: 1145-1152 - [c51]Liu Yang, Rong Jin, Jieping Ye:
Online learning by ellipsoid method. ICML 2009: 1153-1160 - [c50]Shuiwang Ji, Jieping Ye:
Linear Dimensionality Reduction for Multi-label Classification. IJCAI 2009: 1077-1082 - [c49]Jun Liu, Jianhui Chen, Songcan Chen, Jieping Ye:
Learning the Optimal Neighborhood Kernel for Classification. IJCAI 2009: 1144-1149 - [c48]Liang Sun, Shuiwang Ji, Shipeng Yu, Jieping Ye:
On the Equivalence between Canonical Correlation Analysis and Orthonormalized Partial Least Squares. IJCAI 2009: 1230-1235 - [c47]Lei Tang, Jianhui Chen, Jieping Ye:
On Multiple Kernel Learning with Multiple Labels. IJCAI 2009: 1255-1260 - [c46]Zheng Zhao, Liang Sun, Shipeng Yu, Huan Liu, Jieping Ye:
Multiclass Probabilistic Kernel Discriminant Analysis. IJCAI 2009: 1363-1368 - [c45]Ying-Xin Li, Shuiwang Ji, Sudhir Kumar, Jieping Ye, Zhi-Hua Zhou:
DrosophilaGene Expression Pattern Annotation through Multi-Instance Multi-Label Learning. IJCAI 2009: 1445-1450 - [c44]Shuiwang Ji, Lei Yuan, Ying-Xin Li, Zhi-Hua Zhou, Sudhir Kumar, Jieping Ye:
Drosophila gene expression pattern annotation using sparse features and term-term interactions. KDD 2009: 407-416 - [c43]Jun Liu, Jianhui Chen, Jieping Ye:
Large-scale sparse logistic regression. KDD 2009: 547-556 - [c42]Bao-Hong Shen, Shuiwang Ji, Jieping Ye:
Mining discrete patterns via binary matrix factorization. KDD 2009: 757-766 - [c41]Liang Sun, Rinkal Patel, Jun Liu, Kewei Chen, Teresa Wu, Jing Li, Eric Reiman, Jieping Ye:
Mining brain region connectivity for alzheimer's disease study via sparse inverse covariance estimation. KDD 2009: 1335-1344 - [c40]Shuai Huang, Jing Li, Liang Sun, Jun Liu, Teresa Wu, Kewei Chen, Adam Fleisher, Eric Reiman, Jieping Ye:
Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data. NIPS 2009: 808-816 - [c39]Liang Sun, Jun Liu, Jianhui Chen, Jieping Ye:
Efficient Recovery of Jointly Sparse Vectors. NIPS 2009: 1812-1820 - [c38]Jun Liu, Shuiwang Ji, Jieping Ye:
Multi-Task Feature Learning Via Efficient l2, 1-Norm Minimization. UAI 2009: 339-348 - [r2]Jieping Ye, Ravi Janardan, Sudhir Kumar:
Biological Image Analysis via Matrix Approximation. Encyclopedia of Data Warehousing and Mining 2009: 166-170 - [r1]Qi Li, Jieping Ye, Chandra Kambhamettu:
Interest Pixel Mining. Encyclopedia of Data Warehousing and Mining 2009: 1091-1096 - 2008
- [j24]Shuiwang Ji, Liang Sun, Rong Jin, Sudhir Kumar, Jieping Ye:
Automated annotation of Drosophila gene expression patterns using a controlled vocabulary. Bioinform. 24(17): 1881-1888 (2008) - [j23]Liang Sun, Shuiwang Ji, Jieping Ye:
Adaptive diffusion kernel learning from biological networks for protein function prediction. BMC Bioinform. 9 (2008) - [j22]Qi Li, Jieping Ye, Min Li, Chandra Kambhamettu:
Adaptive Appearance Based Face Recognition. Int. J. Artif. Intell. Tools 17(1): 175-193 (2008) - [j21]Qi Li, Chandra Kambhamettu, Jieping Ye:
An evaluation of identity representability of facial expressions using feature distributions. Neurocomputing 71(10-12): 1902-1912 (2008) - [j20]Jieping Ye:
Comments on the Complete Characterization of a Family of Solutions to a Generalized Fisher Criterion. J. Mach. Learn. Res. 9: 517-519 (2008) - [j19]Jieping Ye, Shuiwang Ji, Jianhui Chen:
Multi-class Discriminant Kernel Learning via Convex Programming. J. Mach. Learn. Res. 9: 719-758 (2008) - [j18]Qi Li, Jieping Ye, Chandra Kambhamettu:
Interest point detection using imbalance oriented selection. Pattern Recognit. 41(2): 672-688 (2008) - [j17]Jieping Ye, Jianhui Chen, Ravi Janardan, Sudhir Kumar:
Developmental stage annotation of Drosophila gene expression pattern images via an entire solution path for LDA. ACM Trans. Knowl. Discov. Data 2(1): 4:1-4:21 (2008) - [j16]Shuiwang Ji, Jieping Ye:
Kernel Uncorrelated and Regularized Discriminant Analysis: A Theoretical and Computational Study. IEEE Trans. Knowl. Data Eng. 20(10): 1311-1321 (2008) - [j15]Shuiwang Ji, Jieping Ye:
Generalized Linear Discriminant Analysis: A Unified Framework and Efficient Model Selection. IEEE Trans. Neural Networks 19(10): 1768-1782 (2008) - [c37]Shuiwang Ji, Jieping Ye:
A unified framework for generalized Linear Discriminant Analysis. CVPR 2008 - [c36]Jianhui Chen, Jieping Ye:
Training SVM with indefinite kernels. ICML 2008: 136-143 - [c35]Liang Sun, Shuiwang Ji, Jieping Ye:
A least squares formulation for canonical correlation analysis. ICML 2008: 1024-1031 - [c34]Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Mingrui Wu, Jieping Ye:
Learning subspace kernels for classification. KDD 2008: 106-114 - [c33]Shuiwang Ji, Lei Tang, Shipeng Yu, Jieping Ye:
Extracting shared subspace for multi-label classification. KDD 2008: 381-389 - [c32]Liang Sun, Shuiwang Ji, Jieping Ye:
Hypergraph spectral learning for multi-label classification. KDD 2008: 668-676 - [c31]Zheng Zhao, Jiangxin Wang, Huan Liu, Jieping Ye, Yung Chang:
Identifying biologically relevant genes via multiple heterogeneous data sources. KDD 2008: 839-847 - [c30]Jieping Ye, Kewei Chen, Teresa Wu, Jing Li, Zheng Zhao, Rinkal Patel, Min Bae, Ravi Janardan, Huan Liu, Gene E. Alexander, Eric Reiman:
Heterogeneous data fusion for alzheimer's disease study. KDD 2008: 1025-1033 - [c29]Shuiwang Ji, Liang Sun, Rong Jin, Jieping Ye:
Multi-label Multiple Kernel Learning. NIPS 2008: 777-784 - [e2]M. Arif Wani, Mehmed M. Kantardzic, Tao Li, Ying Liu, Lukasz A. Kurgan, Jieping Ye, Mitsunori Ogihara, Seref Sagiroglu, Xue-wen Chen, Leif E. Peterson, Khalid Hafeez:
The Sixth International Conference on Machine Learning and Applications, ICMLA 2007, Cincinnati, Ohio, USA, 13-15 December 2007. IEEE Computer Society 2008, ISBN 0-7695-3069-9 [contents] - 2007
- [c28]Vineeth Nallure Balasubramanian, Jieping Ye, Sethuraman Panchanathan:
Biased Manifold Embedding: A Framework for Person-Independent Head Pose Estimation. CVPR 2007 - [c27]Jianhui Chen, Jieping Ye, Qi Li:
Integrating Global and Local Structures: A Least Squares Framework for Dimensionality Reduction. CVPR 2007 - [c26]Jieping Ye, Zheng Zhao, Huan Liu:
Adaptive Distance Metric Learning for Clustering. CVPR 2007 - [c25]Jieping Ye:
Least squares linear discriminant analysis. ICML 2007: 1087-1093 - [c24]Jieping Ye, Jianhui Chen, Shuiwang Ji:
Discriminant kernel and regularization parameter learning via semidefinite programming. ICML 2007: 1095-1102 - [c23]Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu:
Nonlinear adaptive distance metric learning for clustering. KDD 2007: 123-132 - [c22]Jieping Ye, Shuiwang Ji, Jianhui Chen:
Learning the kernel matrix in discriminant analysis via quadratically constrained quadratic programming. KDD 2007: 854-863 - [c21]Jieping Ye, Zheng Zhao, Mingrui Wu:
Discriminative K-means for Clustering. NIPS 2007: 1649-1656 - [c20]Jieping Ye, Tao Xiong:
SVM versus Least Squares SVM. AISTATS 2007: 644-651 - 2006
- [j14]Jieping Ye, Tao Xiong:
Computational and Theoretical Analysis of Null Space and Orthogonal Linear Discriminant Analysis. J. Mach. Learn. Res. 7: 1183-1204 (2006) - [j13]Qi Li, Jieping Ye, Chandra Kambhamettu:
Spatial interest pixels (SIPs): useful low-level features of visual media data. Multim. Tools Appl. 30(1): 89-108 (2006) - [j12]Jieping Ye, Ravi Janardan, Qi Li, Haesun Park:
Feature Reduction via Generalized Uncorrelated Linear Discriminant Analysis. IEEE Trans. Knowl. Data Eng. 18(10): 1312-1322 (2006) - [c19]Jieping Ye, Tao Xiong, Qi Li, Ravi Janardan, Jinbo Bi, Vladimir Cherkassky, Chandra Kambhamettu:
Efficient model selection for regularized linear discriminant analysis. CIKM 2006: 532-539 - [c18]Qi Li, Chandra Kambhamettu, Jieping Ye:
Integrating Spatial and Discriminant Strength for Feature Selection and Linear Dimensionality Reduction. CVPR Workshops 2006: 21 - [c17]Tao Xiong, Jieping Ye, Vladimir Cherkassky:
Kernel Uncorrelated and Orthogonal Discriminant Analysis: A Unified Approach. CVPR (1) 2006: 125-131 - [c16]Jieping Ye, Tao Xiong:
Null space versus orthogonal linear discriminant analysis. ICML 2006: 1073-1080 - [c15]Qi Li, Jieping Ye, Min Li, Chandra Kambhamettu:
Adaptive Appearance Based Face Recognition. ICTAI 2006: 677-684 - [c14]Jieping Ye, Tie Wang:
Regularized discriminant analysis for high dimensional, low sample size data. KDD 2006: 454-463 - [c13]Jieping Ye, Tao Xiong, Ravi Janardan:
CPM: A Covariance-preserving Projection Method. SDM 2006: 24-34 - [c12]Jieping Ye, Ivaylo Ilinkin, Ravi Janardan, Adam Isom:
Multiple Structure Alignment and Consensus Identification for Proteins. WABI 2006: 115-125 - [e1]M. Arif Wani, Tao Li, Lukasz A. Kurgan, Jieping Ye, Ying Liu:
The Fifth International Conference on Machine Learning and Applications, ICMLA 2006, Orlando, Florida, USA, 14-16 December 2006. IEEE Computer Society 2006, ISBN 0-7695-2735-3 [contents] - 2005
- [j11]Jieping Ye:
Characterization of a Family of Algorithms for Generalized Discriminant Analysis on Undersampled Problems. J. Mach. Learn. Res. 6: 483-502 (2005) - [j10]Jieping Ye:
Generalized Low Rank Approximations of Matrices. Mach. Learn. 61(1-3): 167-191 (2005) - [j9]Jieping Ye, Qi Li:
A Two-Stage Linear Discriminant Analysis via QR-Decomposition. IEEE Trans. Pattern Anal. Mach. Intell. 27(6): 929-941 (2005) - [j8]Jieping Ye, Qi Li, Hui Xiong, Haesun Park, Ravi Janardan, Vipin Kumar:
IDR/QR: An Incremental Dimension Reduction Algorithm via QR Decomposition. IEEE Trans. Knowl. Data Eng. 17(9): 1208-1222 (2005) - [c11]Chris H. Q. Ding, Jieping Ye:
2-Dimensional Singular Value Decomposition for 2D Maps and Images. SDM 2005: 32-43 - 2004
- [j7]Jieping Ye, Ravi Janardan, Songtao Liu:
Pairwise Protein Structure Alignment Based on an Orientation-independent Backbone Representation. J. Bioinform. Comput. Biol. 2(4): 699-718 (2004) - [j6]Jieping Ye, Ravi Janardan:
Approximate Multiple Protein Structure Alignment Using the Sum-of-Pairs Distance. J. Comput. Biol. 11(5): 986-1000 (2004) - [j5]Jieping Ye, Ravi Janardan, Cheong Hee Park, Haesun Park:
An Optimization Criterion for Generalized Discriminant Analysis on Undersampled Problems. IEEE Trans. Pattern Anal. Mach. Intell. 26(8): 982-994 (2004) - [j4]Jieping Ye, Qi Li:
LDA/QR: an efficient and effective dimension reduction algorithm and its theoretical foundation. Pattern Recognit. 37(4): 851-854 (2004) - [j3]Jieping Ye, Tao Li, Tao Xiong, Ravi Janardan:
Using Uncorrelated Discriminant Analysis for Tissue Classification with Gene Expression Data. IEEE ACM Trans. Comput. Biol. Bioinform. 1(4): 181-190 (2004) - [c10]Qi Li, Jieping Ye, Chandra Kambhamettu:
Linear Projection Methods in Face Recognition under Unconstrained Illuminations: A Comparative Study. CVPR (2) 2004: 474-481 - [c9]Jieping Ye:
Generalized low rank approximations of matrices. ICML 2004 - [c8]Jieping Ye, Ravi Janardan, Qi Li, Haesun Park:
Feature extraction via generalized uncorrelated linear discriminant analysis. ICML 2004 - [c7]Jieping Ye, Ravi Janardan, Qi Li:
GPCA: an efficient dimension reduction scheme for image compression and retrieval. KDD 2004: 354-363 - [c6]Jieping Ye, Qi Li, Hui Xiong, Haesun Park, Ravi Janardan, Vipin Kumar:
IDR/QR: an incremental dimension reduction algorithm via QR decomposition. KDD 2004: 364-373 - [c5]Tao Xiong, Jieping Ye, Qi Li, Ravi Janardan, Vladimir Cherkassky:
Efficient Kernel Discriminant Analysis via QR Decomposition. NIPS 2004: 1529-1536 - [c4]Jieping Ye, Ravi Janardan, Qi Li:
Two-Dimensional Linear Discriminant Analysis. NIPS 2004: 1569-1576 - 2003
- [c3]Qi Li, Jieping Ye, Chandra Kambhamettu:
Spatial Interest Pixels (SIPs): Useful Low-Level Features of Visual Media Data. ICDM 2003: 163-170 - [c2]Jieping Ye, Ravi Janardan, Cheong Hee Park, Haesun Park:
A new optimization criterion for generalized discriminant analysis on undersampled problems. ICDM 2003: 419-426 - [c1]Jieping Ye, Ravi Janardan, Songtao Liu:
Pairwise Protein Structure Alignment Based on an Orientation-Independent Representation of the Backbone Geometry. ICTAI 2003: 2-8 - 2000
- [j2]Ruibin Qu, Jieping Ye:
Approximation of minimum energy curves. Appl. Math. Comput. 108(2-3): 153-166 (2000) - [j1]Ruibin Qu, Jieping Ye:
Efficient approximation of minimum energy curves with interpolatory constraints. Appl. Math. Comput. 109(2-3): 151-166 (2000)
Coauthor Index
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