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2020 – today
- 2024
[j46]Yiqiang Yi
, Xu Wan, Kangfei Zhao, Le Ou-Yang, Peilin Zhao:
Equivariant Line Graph Neural Network for Protein-Ligand Binding Affinity Prediction. IEEE J. Biomed. Health Informatics 28(7): 4336-4347 (2024)- [j45]Shibo Feng, Chunyan Miao, Ke Xu, Jiaxiang Wu, Pengcheng Wu, Yang Zhang, Peilin Zhao:
Multi-Scale Attention Flow for Probabilistic Time Series Forecasting. IEEE Trans. Knowl. Data Eng. 36(5): 2056-2068 (2024) - [c137]Shibo Feng, Chunyan Miao, Zhong Zhang, Peilin Zhao:
Latent Diffusion Transformer for Probabilistic Time Series Forecasting. AAAI 2024: 11979-11987 - [c136]Liang Chen, Yatao Bian, Yang Deng, Deng Cai, Shuaiyi Li, Peilin Zhao, Kam-Fai Wong:
WatME: Towards Lossless Watermarking Through Lexical Redundancy. ACL (1) 2024: 9166-9180 - [c135]Zixuan Liu, Liu Liu, Xueqian Wang, Peilin Zhao:
DFWLayer: Differentiable Frank-Wolfe Optimization Layer. Tiny Papers @ ICLR 2024 - [c134]Yang Liu, Jiashun Cheng, Haihong Zhao, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li, Yu Rong:
SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases. ICLR 2024 - [c133]Binghui Xie, Yatao Bian, Kaiwen Zhou, Yongqiang Chen, Peilin Zhao, Bo Han, Wei Meng, James Cheng:
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations. ICLR 2024 - [c132]Zhipeng Zhou, Liu Liu, Peilin Zhao, Wei Gong:
Pareto Deep Long-Tailed Recognition: A Conflict-Averse Solution. ICLR 2024 - [c131]Shuaicheng Niu, Chunyan Miao, Guohao Chen, Pengcheng Wu, Peilin Zhao:
Test-Time Model Adaptation with Only Forward Passes. ICML 2024 - [c130]Yichen Wu, Hong Wang, Peilin Zhao, Yefeng Zheng, Ying Wei, Long-Kai Huang:
Mitigating Catastrophic Forgetting in Online Continual Learning by Modeling Previous Task Interrelations via Pareto Optimization. ICML 2024 - [i103]Binghui Xie, Yatao Bian, Kaiwen Zhou, Yongqiang Chen, Peilin Zhao, Bo Han, Wei Meng, James Cheng:
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations. CoRR abs/2402.03139 (2024) - [i102]Haoyu Wang, Guozheng Ma, Ziqiao Meng, Zeyu Qin, Li Shen, Zhong Zhang, Bingzhe Wu, Liu Liu, Yatao Bian, Tingyang Xu, Xueqian Wang, Peilin Zhao:
Step-On-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping. CoRR abs/2402.07610 (2024) - [i101]Huan Ma, Yan Zhu, Changqing Zhang, Peilin Zhao, Baoyuan Wu, Long-Kai Huang, Qinghua Hu, Bingzhe Wu:
Invariant Test-Time Adaptation for Vision-Language Model Generalization. CoRR abs/2403.00376 (2024) - [i100]Mingkui Tan, Guohao Chen, Jiaxiang Wu, Yifan Zhang, Yaofo Chen, Peilin Zhao, Shuaicheng Niu:
Uncertainty-Calibrated Test-Time Model Adaptation without Forgetting. CoRR abs/2403.11491 (2024) - [i99]Shuaicheng Niu, Chunyan Miao, Guohao Chen, Pengcheng Wu, Peilin Zhao:
Test-Time Model Adaptation with Only Forward Passes. CoRR abs/2404.01650 (2024) - [i98]Dezhong Yao, Sanmu Li, Yutong Dai, Zhiqiang Xu, Shengshan Hu, Peilin Zhao, Lichao Sun:
Variational Bayes for Federated Continual Learning. CoRR abs/2405.14291 (2024) - [i97]Zhicheng Chen, Xi Xiao, Ke Xu, Zhong Zhang, Yu Rong, Qing Li, Guojun Gan, Zhiqiang Xu, Peilin Zhao:
MGCP: A Multi-Grained Correlation based Prediction Network for Multivariate Time Series. CoRR abs/2405.19661 (2024) - 2023
- [j44]Zhifeng Bao, Panagiotis Bouros, Reynold Cheng, Byron Choi, Anton Dignös, Wei Ding, Yixiang Fang, Boyang Han, Jilin Hu, Arijit Khan, Wenqing Lin, Xuemin Lin, Cheng Long, Nikos Mamoulis, Jian Pei, Matthias Renz, Shashi Shekhar, Jieming Shi, Eleni Tzirita Zacharatou, Sibo Wang, Xiao Wang, Xue Wang, Raymond Chi-Wing Wong, Da Yan, Xifeng Yan, Bin Yang, Dezhong Yao, Ce Zhang, Peilin Zhao, Rong Zhu:
A Summary of ICDE 2022 Research Session Panels. IEEE Data Eng. Bull. 46(4): 4-17 (2023) - [j43]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) - [j42]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) - [j41]Zixuan Liu, Liu Liu, Bingzhe Wu, Lanqing Li, Xueqian Wang, Bo Yuan, Peilin Zhao:
Dynamics Adapted Imitation Learning. Trans. Mach. Learn. Res. 2023 (2023) - [c129]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 - [c128]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 - [c127]Liang Zeng, Lanqing Li, Ziqi Gao, Peilin Zhao, Jian Li:
ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification. AAAI 2023: 11138-11146 - [c126]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 - [c125]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 - [c124]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 - [c123]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 - [c122]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 - [c121]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 - [c120]Wanjin Feng, Hailong Shi, Peilin Zhao, Xingyu Gao:
Mixtron: Bandit Online Multiclass Prediction with Implicit Feedback. ICDM 2023: 1004-1012 - [c119]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 - [c118]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 - [c117]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 - [c116]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 - [c115]Ziqiao Meng, Peilin Zhao, Yang Yu, Irwin King:
Doubly Stochastic Graph-based Non-autoregressive Reaction Prediction. IJCAI 2023: 4064-4072 - [c114]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 - [c113]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 - [c112]Long-Kai Huang, Peilin Zhao, Junzhou Huang, Sinno Jialin Pan:
Retaining Beneficial Information from Detrimental Data for Neural Network Repair. NeurIPS 2023 - [c111]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. NeurIPS 2023 - [c110]Jianheng Tang, Fengrui Hua, Ziqi Gao, Peilin Zhao, Jia Li:
GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection. NeurIPS 2023 - [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,