Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDJieping Ye
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 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) - [c258]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 - [c257]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 - [c256]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 - [c255]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 - [c254]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 - [c253]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 - [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] - [i104]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) - [i103]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) - [i102]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) - [i101]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) - [i100]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) - [i99]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) - [i98]Kai Liu, Sheng Jin, Zhihang Fu, Ze Chen, Rongxin Jiang, Jieping Ye:
Uncertainty-aware Unsupervised Multi-Object Tracking. CoRR abs/2307.15409 (2023) - [i97]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) - 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 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]