A General Offline Reinforcement Learning Framework for Interactive Recommendation T Xiao, D Wang The Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021 | 80 | 2021 |
Learning How to Propagate Messages in Graph Neural Networks T Xiao, Z Chen, D Wang, S Wang ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2021 | 74 | 2021 |
Neural Variational Hybrid Collaborative Filtering T Xiao, S Liang, H Shen, Z Meng arXiv preprint, 2019 | 70* | 2019 |
Decoupled Self-supervised Learning for Graphs T Xiao, Z Chen, Z Guo, Z Zhuang, S Wang NeurIPS 2022, 2022 | 56 | 2022 |
BA-GNN: On Learning Bias-aware Graph Neural Network Z Chen, T Xiao*, K Kuang International Conference on Data Engineering (ICDE), 3012-3024, 2022 | 49 | 2022 |
ISLF: Interest Shift and Latent Factors Combination Model for Session-based Recommendation. J Song, H Shen, Z Ou, J Zhang, T Xiao, S Liang International Joint Conferences on Artificial Intelligence, 2019 | 46 | 2019 |
Semi-supervisedly Co-embedding Attributed Networks Z Meng, S Liang, J Fang, T Xiao NeurIPS 2019, 2019 | 36 | 2019 |
Hierarchical Neural Variational Model for Personalized Sequential Recommendation T Xiao, S Liang, Z Meng The World Wide Web Conference (WWW), 2019 | 34 | 2019 |
Towards Unbiased and Robust Causal Ranking for Recommender Systems T Xiao, S Wang ACM International Conference on Web Search and Data Mining, 2022 | 24 | 2022 |
Bayesian Deep Collaborative Matrix Factorization T Xiao, S Liang, W Shen, Z Meng The Thirty-Third AAAI Conference on Artificial Intelligence, 2019 | 24 | 2019 |
Dynamic Bayesian Metric Learning for Personalized Product Search T Xiao, J Ren, Z Meng, H Sun, S Liang ACM International Conference on Information and Knowledge Management, 2019 | 23 | 2019 |
Simple and Asymmetric Graph Contrastive Learning without Augmentations T Xiao, H Zhu, Z Chen, S Wang NeurIPS 2023, 2023 | 22 | 2023 |
Towards Fair Graph Neural Networks via Graph Counterfactual Z Guo, J Li, T Xiao, Y Ma, S Wang ACM International Conference on Information and Knowledge Management, 2023 | 17 | 2023 |
Counterfactual Learning on Graphs: A Survey Z Guo, T Xiao, Z Wu, C Aggarwal, H Liu, S Wang arXiv preprint arXiv:2304.01391, 2023 | 16 | 2023 |
Learning to Reweight for Graph Neural Network Z Chen, T Xiao, K Kuang, Z Lv, M Zhang, J Yang, C Lu, H Yang, F Wu arXiv preprint arXiv:2312.12475, 2023 | 14* | 2023 |
Representation Matters When Learning from Biased Feedback in Recommendation T Xiao, Z Chen, S Wang ACM International Conference on Information & Knowledge Management, 2022 | 11 | 2022 |
Certifiably Robust Graph Contrastive Learning M Lin, T Xiao, E Dai, X Zhang, S Wang NeurIPS 2023, 2023 | 10 | 2023 |
Reconsidering Learning Objectives in Unbiased Learning with Unobserved Confounders T Xiao, Z Chen, S Wang KDD 2023, 2023 | 10* | 2023 |
Dynamic Collaborative Recurrent Learning T Xiao, S Liang, Z Meng ACM International Conference on Information and Knowledge Management, 2019 | 10 | 2019 |
Fairness-aware Message Passing for Graph Neural Networks H Zhu, G Fu, Z Guo, Z Zhang, T Xiao, S Wang arXiv preprint arXiv:2306.11132, 2023 | 9 | 2023 |