| Towards Understanding the Importance of Noise in Training Neural Networks M Zhou, T Liu, Y Li, D Lin, E Zhou, T Zhao International Conference on Machine Learning, 2019 | 43 | 2019 |
| Deep Reinforcement Learning with Robust and Smooth Policy Y Li*, Q Shen*, H Jiang, Z Wang, T Zhao International Conference on Machine Learning, 2020 | 34* | 2020 |
| Implicit Bias of Gradient Descent based Adversarial Training on Separable Data Y Li, EX Fang, H Xu, T Zhao International Conference on Learning Representations, 2020 | 32* | 2020 |
| Non-convex Conditional Gradient Sliding C Qu, Y Li, H Xu International Conference on Machine Learning, 2017 | 22 | 2017 |
| Homotopic Policy Mirror Descent: Policy Convergence, Implicit Regularization, and Improved Sample Complexity Y Li, G Lan, T Zhao arXiv preprint arXiv:2201.09457, 2022 | 9 | 2022 |
| Permutation Invariant Policy Optimization for Mean-field Multi-agent Reinforcement Learning: A Principled Approach Y Li, L Wang, J Yang, E Wang, Z Wang, T Zhao, H Zha arXiv preprint arXiv:2105.08268, 2021 | 8 | 2021 |
| Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization T Liu, Y Li, S Wei, E Zhou, T Zhao International Conference on Artificial Intelligence and Statistics, 1891-1899, 2021 | 8 | 2021 |
| Pessimism Meets Invariance: Provably Efficient Offline Mean-field Multi-agent RL M Chen, Y Li, E Wang, Z Yang, Z Wang, T Zhao Advances in Neural Information Processing Systems 34, 17913-17926, 2021 | 5 | 2021 |
| First-order Policy Optimization for Robust Markov Decision Process Y Li, T Zhao, G Lan arXiv preprint arXiv:2209.10579, 2022 | 4 | 2022 |
| Residual Network based Direct Synthesis of EM Structures: A Study on One-to-one Transformers D Munzer, S Er, M Chen, Y Li, NS Mannem, T Zhao, H Wang IEEE Radio Frequency Integrated Circuits Symposium (RFIC), 143-146, 2020 | 4 | 2020 |
| Block Policy Mirror Descent G Lan, Y Li, T Zhao arXiv preprint arXiv:2201.05756, 2022 | 3 | 2022 |
| Implicit Regularization of Bregman Proximal Point Algorithm and Mirror Descent on Separable Data Y Li, C Ju, EX Fang, T Zhao arXiv preprint arXiv:2108.06808, 2021 | 2 | 2021 |
| Deep Learning Assisted End-to-End Synthesis of mm-Wave Passive Networks with 3D EM Structures: A Study on A Transformer-Based Matching Network S Er, E Liu, M Chen, Y Li, Y Liu, T Zhao, H Wang 2021 IEEE MTT-S International Microwave Symposium (IMS), 66-69, 2021 | 2 | 2021 |
| Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits Y Li, D Choudhary, X Wei, B Yuan, B Bhushanam, T Zhao, G Lan International Conference on Learning Representations, 2022 | 1 | 2022 |
| Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably T Liu, Y Li, E Zhou, T Zhao International Conference on Artificial Intelligence and Statistics, 2022 | | 2022 |
