| On the landscape of synchronization networks: A perspective from nonconvex optimization S Ling, R Xu, AS Bandeira SIAM Journal on Optimization 29 (3), 1879-1907, 2019 | 75 | 2019 |
| Learn to match with no regret: Reinforcement learning in markov matching markets Y Min, T Wang, R Xu, Z Wang, M Jordan, Z Yang Advances in Neural Information Processing Systems 35, 19956-19970, 2022 | 34 | 2022 |
| Convergence and alignment of gradient descent with random backpropagation weights G Song, R Xu, J Lafferty Advances in Neural Information Processing Systems 34, 19888-19898, 2021 | 21 | 2021 |
| Meta learning in the continuous time limit R Xu, L Chen, A Karbasi International conference on artificial intelligence and statistics, 3052-3060, 2021 | 17 | 2021 |
| Cascaded gaps: Towards logarithmic regret for risk-sensitive reinforcement learning Y Fei, R Xu International Conference on Machine Learning, 6392-6417, 2022 | 14 | 2022 |
| Cascaded gaps: Towards gap-dependent regret for risk-sensitive reinforcement learning Y Fei, R Xu arXiv preprint arXiv:2203.03110, 2022 | 8 | 2022 |
| Finding regularized competitive equilibria of heterogeneous agent macroeconomic models via reinforcement learning R Xu, Y Min, T Wang, MI Jordan, Z Wang, Z Yang International Conference on Artificial Intelligence and Statistics, 375-407, 2023 | 6 | 2023 |
| Noise-adaptive thompson sampling for linear contextual bandits R Xu, Y Min, T Wang Advances in Neural Information Processing Systems 36, 2024 | 5 | 2024 |
| Convergence and alignment of gradient descentwith random back propagation weights G Song, R Xu, J Lafferty arXiv preprint arXiv:2106.06044, 2021 | 3 | 2021 |
| Learning the kernel for classification and regression C Li, L Venturi, R Xu arXiv preprint arXiv:1712.08597, 2017 | 2 | 2017 |
| Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models with Reinforcement Learning R Xu, Y Min, T Wang, Z Wang, MI Jordan, Z Yang arXiv preprint arXiv:2303.04833, 2023 | 1 | 2023 |
| Taming Equilibrium Bias in Risk-Sensitive Multi-Agent Reinforcement Learning Y Fei, R Xu arXiv preprint arXiv:2405.02724, 2024 | | 2024 |
| Optimization and Sequential Decision Making: Implicit Loss Functions and Variance-Aware Reinforcement Learning R Xu Yale University, 2023 | | 2023 |
Tianhao WangResearch Assistant Professor, Toyota Technological Institute at ChicagoBestätigte E-Mail-Adresse bei ttic.edu
