| Kimi k1. 5: Scaling reinforcement learning with llms K Team, A Du, B Gao, B Xing, C Jiang, C Chen, C Li, C Xiao, C Du, C Liao, ... arXiv preprint arXiv:2501.12599, 2025 | 713* | 2025 |
| Estimating mutual information for discrete-continuous mixtures W Gao, S Kannan, S Oh, P Viswanath Advances in neural information processing systems 30, 2017 | 231 | 2017 |
| Label leakage and protection in two-party split learning O Li, J Sun, X Yang, W Gao, H Zhang, J Xie, V Smith, C Wang arXiv preprint arXiv:2102.08504, 2021 | 209 | 2021 |
| Demystifying fixed k-nearest neighbor information estimators W Gao, S Oh, P Viswanath Information Theory (ISIT), 2017 IEEE International Symposium on, 1267-1271, 2017 | 203 | 2017 |
| Seed1. 5-thinking: Advancing superb reasoning models with reinforcement learning BD Seed, J Chen, T Fan, X Liu, L Liu, Z Lin, M Wang, C Wang, X Wei, ... arXiv preprint arXiv:2504.13914, 2025 | 116 | 2025 |
| A predictive machine learning force-field framework for liquid electrolyte development S Gong, Y Zhang, Z Mu, Z Pu, H Wang, X Han, Z Yu, M Chen, T Zheng, ... Nature Machine Intelligence, 1-10, 2025 | 68* | 2025 |
| Learning an end-to-end structure for retrieval in large-scale recommendations W Gao, X Fan, C Wang, J Sun, K Jia, W Xiao, R Ding, X Bin, H Yang, X Liu Proceedings of the 30th ACM international conference on information …, 2021 | 60* | 2021 |
| The nearest neighbor information estimator is adaptively near minimax rate-optimal J Jiao, W Gao, Y Han Advances in neural information processing systems 31, 2018 | 59 | 2018 |
| Vertical federated learning without revealing intersection membership J Sun, X Yang, Y Yao, A Zhang, W Gao, J Xie, C Wang arXiv preprint arXiv:2106.05508, 2021 | 48 | 2021 |
| Rate distortion for model compression: From theory to practice W Gao, YH Liu, C Wang, S Oh International Conference on Machine Learning, 2102-2111, 2019 | 43 | 2019 |
| Enhancing GPU‐Acceleration in the Python‐Based Simulations of Chemistry Frameworks X Wu, Q Sun, Z Pu, T Zheng, W Ma, W Yan, Y Xia, Z Wu, M Huo, X Li, ... Wiley Interdisciplinary Reviews: Computational Molecular Science 15 (2), e70008, 2025 | 42* | 2025 |
| Breaking the bandwidth barrier: Geometrical adaptive entropy estimation W Gao, S Oh, P Viswanath Advances in Neural Information Processing Systems 29, 2016 | 42 | 2016 |
| Defending against reconstruction attack in vertical federated learning J Sun, Y Yao, W Gao, J Xie, C Wang arXiv preprint arXiv:2107.09898, 2021 | 36 | 2021 |
| Learning one-hidden-layer neural networks under general input distributions W Gao, AV Makkuva, S Oh, P Viswanath The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 36 | 2019 |
| Information-theoretic understanding of population risk improvement with model compression Y Bu, W Gao, S Zou, V Veeravalli Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3300-3307, 2020 | 34* | 2020 |
| Density functional estimators with k-nearest neighbor bandwidths W Gao, S Oh, P Viswanath 2017 IEEE International Symposium on Information Theory (ISIT), 1351-1355, 2017 | 19 | 2017 |
| Learning to simulate unseen physical systems with graph neural networks C Yang, W Gao, D Wu, C Wang arXiv preprint arXiv:2201.11976, 2022 | 14 | 2022 |
| Discovering potential correlations via hypercontractivity H Kim, W Gao, S Kannan, S Oh, P Viswanath Advances in Neural Information Processing Systems 30, 2017 | 14 | 2017 |
| One backward from ten forward, subsampling for large-scale deep learning C Dong, X Jin, W Gao, Y Wang, H Zhang, X Wu, J Yang, X Liu arXiv preprint arXiv:2104.13114, 2021 | 13 | 2021 |
| Causal strength via shannon capacity: Axioms, estimators and applications W Gao, S Kannan, S Oh, P Viswanath Proceedings of the 33rd International Conference on Machine Learning, 2016 | 12* | 2016 |
Chong WangAppleVerified email at cs.princeton.edu
