| Provably efficient exploration in policy optimization Q Cai, Z Yang, C Jin, Z Wang International Conference on Machine Learning, 1283-1294, 2020 | 280 | 2020 |
| Neural policy gradient methods: Global optimality and rates of convergence L Wang, Q Cai, Z Yang, Z Wang International Conference on Learning Representations 2020, 2019 | 238 | 2019 |
| Neural Trust Region/Proximal Policy Optimization Attains Globally Optimal Policy B Liu, Q Cai, Z Yang, Z Wang Advances in Neural Information Processing Systems, 10564-10575, 2019 | 206* | 2019 |
| Neural temporal-difference learning converges to global optima Q Cai, Z Yang, JD Lee, Z Wang Advances in Neural Information Processing Systems 32, 2019 | 134* | 2019 |
| On the Global Optimality of Model-Agnostic Meta-Learning: Reinforcement Learning and Supervised Learning L Wang, Q Cai, Z Yang, Z Wang International Conference on Machine Learning, 9837-9846, 2020 | 40 | 2020 |
| On the global convergence of imitation learning: A case for linear quadratic regulator Q Cai, M Hong, Y Chen, Z Wang arXiv preprint arXiv:1901.03674, 2019 | 34 | 2019 |
| Generative adversarial imitation learning with neural network parameterization: Global optimality and convergence rate Y Zhang, Q Cai, Z Yang, Z Wang International conference on machine learning, 11044-11054, 2020 | 28* | 2020 |
| Reinforcement learning from partial observation: Linear function approximation with provable sample efficiency Q Cai, Z Yang, Z Wang International Conference on Machine Learning, 2485-2522, 2022 | 24* | 2022 |
| Embed to control partially observed systems: Representation learning with provable sample efficiency L Wang, Q Cai, Z Yang, Z Wang arXiv preprint arXiv:2205.13476, 2022 | 17 | 2022 |
| Provably efficient offline reinforcement learning for partially observable markov decision processes H Guo, Q Cai, Y Zhang, Z Yang, Z Wang International Conference on Machine Learning, 8016-8038, 2022 | 15 | 2022 |
| Can Temporal-Difference and Q-Learning Learn Representation? A Mean-Field Theory Y Zhang, Q Cai, Z Yang, Y Chen, Z Wang Advances in Neural Information Processing Systems 33, 19680-19692, 2020 | 15 | 2020 |
| An analysis of attention via the lens of exchangeability and latent variable models Y Zhang, B Liu, Q Cai, L Wang, Z Wang arXiv preprint arXiv:2212.14852, 2022 | 7 | 2022 |
| Neural temporal difference and q learning provably converge to global optima Q Cai, Z Yang, JD Lee, Z Wang Mathematics of Operations Research 49 (1), 619-651, 2024 | 4 | 2024 |
| Optimistic policy optimization with general function approximations Q Cai, Z Yang, C Szepesvari, Z Wang | 2 | 2020 |
| Represent to Control Partially Observed Systems: Representation Learning with Provable Sample Efficiency L Wang, Q Cai, Z Yang, Z Wang The Eleventh International Conference on Learning Representations, 0 | 1* | |
| Provably Efficient Reinforcement Learning Q Cai Northwestern University, 2022 | | 2022 |
| BooVI: Provably Efficient Bootstrapped Value Iteration B Liu, Q Cai, Z Yang, Z Wang Advances in Neural Information Processing Systems 34, 7041-7053, 2021 | | 2021 |
