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2020 – today
- 2023
[j42]Xuguang Duan
, Xin Wang, Peilin Zhao, Guangyao Shen, Wenwu Zhu:
DeepLogic: Joint Learning of Neural Perception and Logical Reasoning. IEEE Trans. Pattern Anal. Mach. Intell. 45(4): 4321-4334 (2023)- [j41]Wendi Wu, Zongren Li, Yawei Zhao, Chen Yu, Peilin Zhao, Ji Liu, Kunlun He:
Decentralized Online Learning: Take Benefits from Others' Data without Sharing Your Own to Track Global Trend. ACM Trans. Intell. Syst. Technol. 14(1): 13:1-13:22 (2023) - [c125]Ziqi Gao, Yifan Niu, Jiashun Cheng, Jianheng Tang, Lanqing Li, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li:
Handling Missing Data via Max-Entropy Regularized Graph Autoencoder. AAAI 2023: 7651-7659 - [c124]Yuanfeng Ji, Lu Zhang, Jiaxiang Wu, Bingzhe Wu, Lanqing Li, Long-Kai Huang, Tingyang Xu, Yu Rong, Jie Ren, Ding Xue, Houtim Lai, Wei Liu, Junzhou Huang, Shuigeng Zhou, Ping Luo, Peilin Zhao, Yatao Bian:
DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery - a Focus on Affinity Prediction Problems with Noise Annotations. AAAI 2023: 8023-8031 - [c123]Liang Zeng, Lanqing Li, Ziqi Gao, Peilin Zhao, Jian Li:
ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification. AAAI 2023: 11138-11146 - [c122]Qichao Wang, Huan Ma, Wentao Wei, Hangyu Li, Changqing Zhang, Peilin Zhao, Binwen Zhao, Bo Hu, Shu Zhang, Bingzhe Wu, Liang Chen:
Attention Paper: How Generative AI Reshapes Digital Shadow Industry? ACM TUR-C 2023: 143-144 - [c121]Kangfei Zhao, Yu Rong, Biaobin Jiang, Jianheng Tang, Hengtong Zhang, Jeffrey Xu Yu, Peilin Zhao:
Geometric Graph Learning for Protein Mutation Effect Prediction. CIKM 2023: 3412-3422 - [c120]Yong Guo, Yaofo Chen, Yin Zheng, Qi Chen, Peilin Zhao, Junzhou Huang, Jian Chen, Mingkui Tan:
Pareto-aware Neural Architecture Generation for Diverse Computational Budgets. CVPR Workshops 2023: 2248-2258 - [c119]Zhipeng Zhou, Lanqing Li, Peilin Zhao, Pheng-Ann Heng, Wei Gong:
Class-Conditional Sharpness-Aware Minimization for Deep Long-Tailed Recognition. CVPR 2023: 3499-3509 - [c118]Deng-Bao Wang, Lanqing Li, Peilin Zhao, Pheng-Ann Heng, Min-Ling Zhang:
On the Pitfall of Mixup for Uncertainty Calibration. CVPR 2023: 7609-7618 - [c117]Yifan Zhang, Peilin Zhao, Qingyao Wu, Bin Li, Junzhou Huang, Mingkui Tan:
Cost-Sensitive Portfolio Selection via Deep Reinforcement Learning (Extended Abstract). ICDE 2023: 3771-3772 - [c116]Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Bingzhe Wu, Yonggang Zhang, Kaili Ma, Han Yang, Peilin Zhao, Bo Han, James Cheng:
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization. ICLR 2023 - [c115]Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang, Zhiquan Wen, Yaofo Chen, Peilin Zhao, Mingkui Tan:
Towards Stable Test-time Adaptation in Dynamic Wild World. ICLR 2023 - [c114]Fu-Yun Wang, Da-Wei Zhou, Liu Liu, Han-Jia Ye, Yatao Bian, De-Chuan Zhan, Peilin Zhao:
BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion. ICLR 2023 - [c113]Songtao Liu, Zhengkai Tu, Minkai Xu, Zuobai Zhang, Lu Lin, Rex Ying, Jian Tang, Peilin Zhao, Dinghao Wu:
FusionRetro: Molecule Representation Fusion via In-Context Learning for Retrosynthetic Planning. ICML 2023: 22028-22041 - [c112]Ziqiao Meng, Peilin Zhao, Yang Yu, Irwin King:
Doubly Stochastic Graph-based Non-autoregressive Reaction Prediction. IJCAI 2023: 4064-4072 - [c111]Ziqiao Meng, Peilin Zhao, Yang Yu, Irwin King:
A Unified View of Deep Learning for Reaction and Retrosynthesis Prediction: Current Status and Future Challenges. IJCAI 2023: 6723-6731 - [c110]Zeyu Cao, Zhipeng Liang, Bingzhe Wu, Shu Zhang, Hangyu Li, Ouyang Wen, Yu Rong, Peilin Zhao:
Privacy Matters: Vertical Federated Linear Contextual Bandits for Privacy Protected Recommendation. KDD 2023: 154-166 - [c109]Zerun Lin, Yuhan Zhang, Lixin Duan, Le Ou-Yang, Peilin Zhao:
MoVAE: A Variational AutoEncoder for Molecular Graph Generation. SDM 2023: 514-522 - [c108]Ziqiao Meng, Yaoman Li, Peilin Zhao, Yang Yu, Irwin King:
Meta-Learning with Motif-based Task Augmentation for Few-Shot Molecular Property Prediction. SDM 2023: 811-819 - [c107]Hanwen Liu, Peilin Zhao, Tingyang Xu, Yatao Bian, Junzhou Huang, Yuesheng Zhu, Yadong Mu:
Curriculum Graph Poisoning. WWW 2023: 2011-2021 - [i96]Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang, Zhiquan Wen, Yaofo Chen, Peilin Zhao, Mingkui Tan:
Towards Stable Test-Time Adaptation in Dynamic Wild World. CoRR abs/2302.12400 (2023) - [i95]Ziniu Li, Ke Xu, Liu Liu, Lanqing Li, Deheng Ye, Peilin Zhao:
Deploying Offline Reinforcement Learning with Human Feedback. CoRR abs/2303.07046 (2023) - [i94]Huan Ma, Changqing Zhang, Yatao Bian, Lemao Liu, Zhirui Zhang, Peilin Zhao, Shu Zhang, Huazhu Fu, Qinghua Hu, Bingzhe Wu:
Fairness-guided Few-shot Prompting for Large Language Models. CoRR abs/2303.13217 (2023) - [i93]Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Qinghua Hu, Bingzhe Wu, Changqing Zhang, Jianhua Yao:
Reweighted Mixup for Subpopulation Shift. CoRR abs/2304.04148 (2023) - [i92]Yuanfeng Ji, Yatao Bian, Guoji Fu, Peilin Zhao, Ping Luo:
SyNDock: N Rigid Protein Docking via Learnable Group Synchronization. CoRR abs/2305.15156 (2023) - [i91]Qichao Wang, Huan Ma, Wentao Wei, Hangyu Li, Liang Chen, Peilin Zhao, Binwen Zhao, Bo Hu, Shu Zhang, Zibin Zheng, Bingzhe Wu:
Attention Paper: How Generative AI Reshapes Digital Shadow Industry? CoRR abs/2305.18346 (2023) - [i90]Ziqiao Meng, Peilin Zhao, Yang Yu, Irwin King:
Doubly Stochastic Graph-based Non-autoregressive Reaction Prediction. CoRR abs/2306.06119 (2023) - [i89]Jianheng Tang, Fengrui Hua, Ziqi Gao, Peilin Zhao, Jia Li:
GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection. CoRR abs/2306.12251 (2023) - [i88]Ziqiao Meng, Peilin Zhao, Yang Yu, Irwin King:
A Unified View of Deep Learning for Reaction and Retrosynthesis Prediction: Current Status and Future Challenges. CoRR abs/2306.15890 (2023) - [i87]Peng Tang, Zhiqiang Xu, Pengfei Wei, Xiaobin Hu, Peilin Zhao, Xin Cao, Chunlai Zhou, Tobias Lasser:
SR-R2KAC: Improving Single Image Defocus Deblurring. CoRR abs/2307.16242 (2023) - [i86]Zixuan Liu, Liu Liu, Xueqian Wang, Peilin Zhao:
Differentiable Frank-Wolfe Optimization Layer. CoRR abs/2308.10806 (2023) - [i85]Yang Liu, Jiashun Cheng, Haihong Zhao, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li, Yu Rong:
Physics-Inspired Neural Graph ODE for Long-term Dynamical Simulation. CoRR abs/2308.13212 (2023) - [i84]Haoyu Wang, Guozheng Ma, Cong Yu, Ning Gui, Linrui Zhang, Zhiqi Huang, Suwei Ma, Yongzhe Chang, Sen Zhang, Li Shen, Xueqian Wang, Peilin Zhao, Dacheng Tao:
Are Large Language Models Really Robust to Word-Level Perturbations? CoRR abs/2309.11166 (2023) - [i83]Huan Ma, Changqing Zhang, Huazhu Fu, Peilin Zhao, Bingzhe Wu:
Adapting Large Language Models for Content Moderation: Pitfalls in Data Engineering and Supervised Fine-tuning. CoRR abs/2310.03400 (2023) - [i82]Yiqiang Yi, Xu Wan, Yatao Bian, Le Ou-Yang, Peilin Zhao:
ETDock: A Novel Equivariant Transformer for Protein-Ligand Docking. CoRR abs/2310.08061 (2023) - [i81]Yihuai Lan, Zhiqiang Hu, Lei Wang, Yang Wang, Deheng Ye, Peilin Zhao, Ee-Peng Lim, Hui Xiong, Hao Wang:
LLM-Based Agent Society Investigation: Collaboration and Confrontation in Avalon Gameplay. CoRR abs/2310.14985 (2023) - [i80]Liang Chen, Yatao Bian, Yang Deng, Shuaiyi Li, Bingzhe Wu, Peilin Zhao, Kam-Fai Wong:
X-Mark: Towards Lossless Watermarking Through Lexical Redundancy. CoRR abs/2311.09832 (2023) - 2022
- [j40]Runhao Zeng, Wenbing Huang, Mingkui Tan, Yu Rong, Peilin Zhao, Junzhou Huang, Chuang Gan:
Graph Convolutional Module for Temporal Action Localization in Videos. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 6209-6223 (2022) - [j39]Yong Guo, Yin Zheng, Mingkui Tan, Qi Chen, Zhipeng Li, Jian Chen, Peilin Zhao, Junzhou Huang:
Towards Accurate and Compact Architectures via Neural Architecture Transformer. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 6501-6516 (2022) - [j38]Yifan Zhang, Peilin Zhao, Qingyao Wu, Bin Li, Junzhou Huang, Mingkui Tan:
Cost-Sensitive Portfolio Selection via Deep Reinforcement Learning. IEEE Trans. Knowl. Data Eng. 34(1): 236-248 (2022) - [j37]Peng Han, Shuo Shang, Aixin Sun, Peilin Zhao, Kai Zheng, Xiangliang Zhang:
Point-of-Interest Recommendation With Global and Local Context. IEEE Trans. Knowl. Data Eng. 34(11): 5484-5495 (2022) - [j36]Deheng Ye, Guibin Chen, Peilin Zhao, Fuhao Qiu, Bo Yuan, Wen Zhang, Sheng Chen, Mingfei Sun, Xiaoqian Li, Siqin Li, Jing Liang, Zhenjie Lian, Bei Shi, Liang Wang, Tengfei Shi, Qiang Fu, Wei Yang, Lanxiao Huang:
Supervised Learning Achieves Human-Level Performance in MOBA Games: A Case Study of Honor of Kings. IEEE Trans. Neural Networks Learn. Syst. 33(3): 908-918 (2022) - [c106]Peng Han, Peilin Zhao, Chan Lu, Junzhou Huang, Jiaxiang Wu, Shuo Shang, Bin Yao, Xiangliang Zhang:
GNN-Retro: Retrosynthetic Planning with Graph Neural Networks. AAAI 2022: 4014-4021 - [c105]Jiawei Li, Fan Yang, Fang Wang, Yu Rong, Peilin Zhao, Shizhan Chen, Jianhua Yao, Jijun Tang, Fei Guo:
Integrating Prior Knowledge with Graph Encoder for Gene Regulatory Inference from Single-cell RNA-Seq Data. BIBM 2022: 102-107 - [c104]Yicheng Qian, Weixin Luo, Dongze Lian, Xu Tang, Peilin Zhao, Shenghua Gao:
SVIP: Sequence VerIfication for Procedures in Videos. CVPR 2022: 19858-19870 - [c103]Guoji Fu, Peilin Zhao, Yatao Bian:
p-Laplacian Based Graph Neural Networks. ICML 2022: 6878-6917 - [c102]Songtao Liu, Rex Ying, Hanze Dong, Lanqing Li, Tingyang Xu, Yu Rong, Peilin Zhao, Junzhou Huang, Dinghao Wu:
Local Augmentation for Graph Neural Networks. ICML 2022: 14054-14072 - [c101]Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang, Yaofo Chen, Shijian Zheng, Peilin Zhao, Mingkui Tan:
Efficient Test-Time Model Adaptation without Forgetting. ICML 2022: 16888-16905 - [c100]Kuangqi Zhou, Kaixin Wang, Jian Tang, Jiashi Feng, Bryan Hooi, Peilin Zhao, Tingyang Xu, Xinchao Wang:
Jointly Modelling Uncertainty and Diversity for Active Molecular Property Prediction. LoG 2022: 29 - [c99]Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Bingzhe Wu, Changqing Zhang, Jianhua Yao:
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup. NeurIPS 2022 - [c98]Zijing Ou, Tingyang Xu, Qinliang Su, Yingzhen Li, Peilin Zhao, Yatao Bian:
Learning Neural Set Functions Under the Optimal Subset Oracle. NeurIPS 2022 - [c97]Erxue Min, Yu Rong, Tingyang Xu, Yatao Bian, Da Luo, Kangyi Lin, Junzhou Huang, Sophia Ananiadou, Peilin Zhao:
Neighbour Interaction based Click-Through Rate Prediction via Graph-masked Transformer. SIGIR 2022: 353-362 - [c96]Chengqian Gao, Ke Xu, Kuangqi Zhou, Lanqing Li, Xueqian Wang, Bo Yuan, Peilin Zhao:
Value Penalized Q-Learning for Recommender Systems. SIGIR 2022: 2008-2012 - [c95]Erxue Min, Yu Rong, Yatao Bian, Tingyang Xu, Peilin Zhao, Junzhou Huang, Sophia Ananiadou:
Divide-and-Conquer: Post-User Interaction Network for Fake News Detection on Social Media. WWW 2022: 1148-1158 - [i79]Yuanfeng Ji, Lu Zhang, Jiaxiang Wu, Bingzhe Wu, Long-Kai Huang, Tingyang Xu, Yu Rong, Lanqing Li, Jie Ren, Ding Xue, Houtim Lai, Shaoyong Xu, Jing Feng, Wei Liu, Ping Luo, Shuigeng Zhou, Junzhou Huang, Peilin Zhao, Yatao Bian:
DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery - A Focus on Affinity Prediction Problems with Noise Annotations. CoRR abs/2201.09637 (2022) - [i78]Erxue Min, Yu Rong, Tingyang Xu, Yatao Bian, Peilin Zhao, Junzhou Huang, Da Luo, Kangyi Lin, Sophia Ananiadou:
Masked Transformer for Neighhourhood-aware Click-Through Rate Prediction. CoRR abs/2201.13311 (2022) - [i77]Erxue Min, Runfa Chen, Yatao Bian, Tingyang Xu, Kangfei Zhao, Wenbing Huang, Peilin Zhao, Junzhou Huang, Sophia Ananiadou, Yu Rong:
Transformer for Graphs: An Overview from Architecture Perspective. CoRR abs/2202.08455 (2022) - [i76]Zijing Ou, Tingyang Xu, Qinliang Su, Yingzhen Li, Peilin Zhao, Yatao Bian:
Learning Set Functions Under the Optimal Subset Oracle via Equivariant Variational Inference. CoRR abs/2203.01693 (2022) - [i75]Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang, Guanghui Xu, Haokun Li, Peilin Zhao, Junzhou Huang, Yaowei Wang, Mingkui Tan:
Boost Test-Time Performance with Closed-Loop Inference. CoRR abs/2203.10853 (2022) - [i74]Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang, Yaofo Chen, Shijian Zheng, Peilin Zhao, Mingkui Tan:
Efficient Test-Time Model Adaptation without Forgetting. CoRR abs/2204.02610 (2022) - [i73]Bingzhe Wu, Zhipeng Liang, Yuxuan Han, Yatao Bian, Peilin Zhao, Junzhou Huang:
DRFLM: Distributionally Robust Federated Learning with Inter-client Noise via Local Mixup. CoRR abs/2204.07742 (2022) - [i72]Qianggang Ding, Deheng Ye, Tingyang Xu, Peilin Zhao:
GPN: A Joint Structural Learning Framework for Graph Neural Networks. CoRR abs/2205.05964 (2022) - [i71]Shibo Feng, Ke Xu, Jiaxiang Wu, Pengcheng Wu, Fan Lin, Peilin Zhao:
Multi-scale Attention Flow for Probabilistic Time Series Forecasting. CoRR abs/2205.07493 (2022) - [i70]Bingzhe Wu, Jintang Li, Junchi Yu, Yatao Bian, Hengtong Zhang, Chaochao Chen, Chengbin Hou, Guoji Fu, Liang Chen, Tingyang Xu, Yu Rong, Xiaolin Zheng, Junzhou Huang, Ran He, Baoyuan Wu, Guangyu Sun, Peng Cui, Zibin Zheng, Zhe Liu, Peilin Zhao:
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. CoRR abs/2205.10014 (2022) - [i69]Liang Zeng, Lanqing Li, Ziqi Gao, Peilin Zhao, Jian Li:
ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification. CoRR abs/2205.11332 (2022) - [i68]Ke Xu, Jianqiao Wangni, Yifan Zhang, Deheng Ye, Jiaxiang Wu, Peilin Zhao:
Quantized Adaptive Subgradient Algorithms and Their Applications. CoRR abs/2208.05631 (2022) - [i67]Lanqing Li, Liang Zeng, Ziqi Gao, Shen Yuan, Yatao Bian, Bingzhe Wu, Hengtong Zhang, Chan Lu, Yang Yu, Wei Liu, Hongteng Xu, Jia Li, Peilin Zhao, Pheng-Ann Heng:
ImDrug: A Benchmark for Deep Imbalanced Learning in AI-aided Drug Discovery. CoRR abs/2209.07921 (2022) - [i66]Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Bingzhe Wu, Changqing Zhang, Jianhua Yao:
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup. CoRR abs/2209.08928 (2022) - [i65]Jiahan Liu, Chaochao Yan, Yang Yu, Chan Lu, Junzhou Huang, Le Ou-Yang, Peilin Zhao:
MARS: A Motif-based Autoregressive Model for Retrosynthesis Prediction. CoRR abs/2209.13178 (2022) - [i64]Songtao Liu, Rex Ying, Zuobai Zhang, Peilin Zhao, Jian Tang, Lu Lin, Dinghao Wu:
Metro: Memory-Enhanced Transformer for Retrosynthetic Planning via Reaction Tree. CoRR abs/2209.15315 (2022) - [i63]Yong Guo, Yaofo Chen, Yin Zheng, Qi Chen, Peilin Zhao, Jian Chen, Junzhou Huang, Mingkui Tan:
Pareto-aware Neural Architecture Generation for Diverse Computational Budgets. CoRR abs/2210.07634 (2022) - [i62]Chengqian Gao, Ke Xu, Liu Liu, Deheng Ye, Peilin Zhao, Zhiqiang Xu:
Robust Offline Reinforcement Learning with Gradient Penalty and Constraint Relaxation. CoRR abs/2210.10469 (2022) - [i61]Zeyu Cao, Zhipeng Liang, Shu Zhang, Hangyu Li, Ouyang Wen, Yu Rong, Peilin Zhao, Bingzhe Wu:
Vertical Federated Linear Contextual Bandits. CoRR abs/2210.11050 (2022) - [i60]Yiqiang Yi, Xu Wan, Kangfei Zhao, Le Ou-Yang, Peilin Zhao:
Predicting Protein-Ligand Binding Affinity with Equivariant Line Graph Network. CoRR abs/2210.16098 (2022) - [i59]Ziqi Gao, Yifan Niu, Jiashun Cheng, Jianheng Tang, Tingyang Xu, Peilin Zhao, Lanqing Li, Fugee Tsung, Jia Li:
Handling Missing Data via Max-Entropy Regularized Graph Autoencoder. CoRR abs/2211.16771 (2022) - 2021
- [j35]Guangxia Li, Jia Liu, Xiao Lu, Peilin Zhao, Yulong Shen, Dusit Niyato:
Decentralized Online Learning With Compressed Communication for Near-Sensor Data Analytics. IEEE Commun. Lett. 25(9): 2958-2962 (2021) - [j34]Xiaoli Li, Peilin Zhao, Min Wu, Zhenghua Chen, Le Zhang:
Deep learning for human activity recognition. Neurocomputing 444: 214-216 (2021) - [j33]Kelong Mao, Xi Xiao, Tingyang Xu, Yu Rong, Junzhou Huang, Peilin Zhao:
Molecular graph enhanced transformer for retrosynthesis prediction. Neurocomputing 457: 193-202 (2021) - [j32]Steven C. H. Hoi, Doyen Sahoo, Jing Lu, Peilin Zhao:
Online learning: A comprehensive survey. Neurocomputing 459: 249-289 (2021) - [j31]Zhibin Hu, Jiachun Wang, Yan Yan, Peilin Zhao, Jian Chen, Jin Huang:
Neural graph personalized ranking for Top-N Recommendation. Knowl. Based Syst. 213: 106426 (2021) - [j30]Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang, Yong Guo, Peilin Zhao, Junzhou Huang, Mingkui Tan:
Disturbance-immune weight sharing for neural architecture search. Neural Networks 144: 553-564 (2021) - [j29]Yifan Zhang, Peilin Zhao, Shuaicheng Niu, Qingyao Wu, Jiezhang Cao, Junzhou Huang, Mingkui Tan:
Online Adaptive Asymmetric Active Learning With Limited Budgets. IEEE Trans. Knowl. Data Eng. 33(6): 2680-2692 (2021) - [c94]Qin Wang, Boyuan Wang, Zhenlei Xu, Jiaxiang Wu, Peilin Zhao, Zhen Li, Sheng Wang, Junzhou Huang, Shuguang Cui:
PSSM-Distil: Protein Secondary Structure Prediction (PSSP) on Low-Quality PSSM by Knowledge Distillation with Contrastive Learning. AAAI 2021: 617-625 - [c93]Jinyu Yang, Peilin Zhao, Yu Rong, Chaochao Yan, Chunyuan Li, Hehuan Ma, Junzhou Huang:
Hierarchical Graph Capsule Network. AAAI 2021: 10603-10611 - [c92]Congliang Chen, Jiawei Zhang, Li Shen, Peilin Zhao, Zhi-Quan Luo:
Communication Efficient Primal-Dual Algorithm for Nonconvex Nonsmooth Distributed Optimization. AISTATS 2021: 1594-1602 - [c91]Jinyu Yang, Chunyuan Li, Weizhi An, Hehuan Ma, Yuzhi Guo, Yu Rong, Peilin Zhao, Junzhou Huang:
Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation. ICCV 2021: 9174-9183 - [c90]Shuaicheng Niu, Jiaxiang Wu, Guanghui Xu, Yifan Zhang, Yong Guo, Peilin Zhao, Peng Wang, Mingkui Tan:
AdaXpert: Adapting Neural Architecture for Growing Data. ICML 2021: 8184-8194 - [c89]Ying Wei, Peilin Zhao, Junzhou Huang:
Meta-learning Hyperparameter Performance Prediction with Neural Processes. ICML 2021: 11058-11067 - [c88]Minli Li, Peilin Zhao, Yifan Zhang, Shuaicheng Niu, Qingyao Wu, Mingkui Tan:
Structure-aware Mathematical Expression Recognition with Sequence-Level Modeling. ACM Multimedia 2021: 5038-5046 - [c87]Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Chelsea Finn:
Meta-learning with an Adaptive Task Scheduler. NeurIPS 2021: 7497-7509 - [c86]Jinyu Yang, Weizhi An, Chaochao Yan, Peilin Zhao, Junzhou Huang:
Context-Aware Domain Adaptation in Semantic Segmentation. WACV 2021: 514-524 - [i58]Yong Guo, Yin Zheng, Mingkui Tan, Qi Chen, Zhipeng Li, Jian Chen, Peilin Zhao, Junzhou Huang:
Towards Accurate and Compact Architectures via Neural Architecture Transformer. CoRR abs/2102.10301 (2021) - [i57]Yong Guo, Yaofo Chen, Yin Zheng, Qi Chen, Peilin Zhao, Jian Chen, Junzhou Huang, Mingkui Tan:
Pareto-Frontier-aware Neural Architecture Generation for Diverse Budgets. CoRR abs/2103.00219 (2021) - [i56]Chaoyang He, Keshav Balasubramanian, Emir Ceyani, Yu Rong, Peilin Zhao, Junzhou Huang, Murali Annavaram, Salman Avestimehr:
FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks. CoRR abs/2104.07145 (2021) - [i55]Dezhong Yao, Peilin Zhao, Chen Yu, Hai Jin, Bin Li:
Sparse online relative similarity learning. CoRR abs/2104.07501 (2021) - [i54]Jinyu Yang, Chunyuan Li, Weizhi An, Hehuan Ma, Yuzhi Guo, Yu Rong, Peilin Zhao, Junzhou Huang:
Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation. CoRR abs/2105.10843 (2021) - [i53]Hongteng Xu, Peilin Zhao, Junzhou Huang, Dixin Luo:
Learning Graphon Autoencoders for Generative Graph Modeling. CoRR abs/2105.14244 (2021) - [i52]Shuaicheng Niu, Jiaxiang Wu, Guanghui Xu, Yifan Zhang, Yong Guo, Peilin Zhao, Peng Wang, Mingkui Tan:
AdaXpert: Adapting Neural Architecture for Growing Data. CoRR abs/2107.00254 (2021) - [i51]Songtao Liu, Hanze Dong, Lanqing Li, Tingyang Xu, Yu Rong, Peilin Zhao, Junzhou Huang, Dinghao Wu:
Local Augmentation for Graph Neural Networks. CoRR abs/2109.03856 (2021) - [i50]Chengqian Gao, Ke Xu, Peilin Zhao:
Value Penalized Q-Learning for Recommender Systems. CoRR abs/2110.07923 (2021) - [i49]Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Chelsea Finn:
Meta-learning with an Adaptive Task Scheduler. CoRR abs/2110.14057 (2021) - [i48]Guoji Fu, Peilin Zhao, Yatao Bian:
p-Laplacian Based Graph Neural Networks. CoRR abs/2111.07337 (2021) - [i47]Runhao Zeng, Wenbing Huang, Mingkui Tan, Yu Rong, Peilin Zhao, Junzhou Huang, Chuang Gan:
Graph Convolutional Module for Temporal Action Localization in Videos. CoRR abs/2112.00302 (2021) - [i46]Yicheng Qian, Weixin Luo, Dongze Lian, Xu Tang, Peilin Zhao, Shenghua Gao:
SVIP: Sequence VerIfication for Procedures in Videos. CoRR abs/2112.06447 (2021) - [i45]Chaochao Yan, Peilin Zhao, Chan Lu, Yang Yu, Junzhou Huang:
RetroComposer: Discovering Novel Reactions by Composing Templates for Retrosynthesis Prediction. CoRR abs/2112.11225 (2021) - 2020
- [j28]Xuefei Ning, Yin Zheng, Zhuxi Jiang, Yu Wang, Huazhong Yang, Junzhou Huang, Peilin Zhao:
Nonparametric Topic Modeling with Neural Inference. Neurocomputing 399: 296-306 (2020) - [j27]Guangxia Li, Peilin Zhao, Tao Mei, Peng Yang, Yulong Shen, Kuiyu Chang, Steven C. H. Hoi:
Collaborative online ranking algorithms for multitask learning. Knowl. Inf. Syst. 62(6): 2327-2348 (2020) - [j26]Yifan Zhang, Ying Wei, Qingyao Wu, Peilin Zhao, Shuaicheng Niu, Junzhou Huang, Mingkui Tan:
Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis. IEEE Trans. Image Process. 29: 7834-7844 (2020) - [j25]Peilin Zhao, Dayong Wang, Pengcheng Wu, Steven C. H. Hoi:
A Unified Framework for Sparse Online Learning. ACM Trans. Knowl. Discov. Data 14(5): 59:1-59:20 (2020) - [j24]Xiaoshuang Chen, Yin Zheng, Peilin Zhao, Zhuxi Jiang, Wenye Ma, Junzhou Huang:
A Generalized Locally Linear Factorization Machine with Supervised Variational Encoding. IEEE Trans. Knowl. Data Eng. 32(6): 1036-1049 (2020) - [c85]Tian Bian, Xi Xiao, Tingyang Xu, Peilin Zhao, Wenbing Huang, Yu Rong, Junzhou Huang:
Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks. AAAI 2020: 549-556 - [c84]