| Biased Stochastic First-Order Methods for Conditional Stochastic Optimization and Applications in Meta Learning Y Hu, S Zhang, X Chen, N He Advances in Neural Information Processing Systems 33, 2020 | 68* | 2020 |
| Sample complexity of sample average approximation for conditional stochastic optimization Y Hu, X Chen, N He SIAM Journal on Optimization 30 (3), 2103-2133, 2020 | 29 | 2020 |
| On the Bias-Variance-Cost Tradeoff of Stochastic Optimization Y Hu, X Chen, N He Advances in Neural Information Processing Systems 34, 2021 | 26 | 2021 |
| Distributionally robust model-based reinforcement learning with large state spaces SS Ramesh, PG Sessa, Y Hu, A Krause, I Bogunovic International Conference on Artificial Intelligence and Statistics, 100-108, 2024 | 5 | 2024 |
| Generalization Bounds of Nonconvex-(Strongly)-Concave Stochastic Minimax Optimization S Zhang, Y Hu, L Zhang, N He International Conference on Artificial Intelligence and Statistics, 694-702, 2024 | 3* | 2024 |
| Contextual stochastic bilevel optimization Y Hu, J Wang, Y Xie, A Krause, D Kuhn Advances in Neural Information Processing Systems 36, 2024 | 3 | 2024 |
| Stochastic Optimization under Hidden Convexity I Fatkhullin, N He, Y Hu arXiv preprint arXiv:2401.00108, 2023 | 1 | 2023 |
| Efficient Algorithms for Minimizing Compositions of Convex Functions and Random Functions and Its Applications in Network Revenue Management X Chen, N He, Y Hu, Z Ye arXiv preprint arXiv:2205.01774, 2022 | 1 | 2022 |
| Stochastic optimization with biased oracles and hidden convexity Y Hu | | 2022 |
Niao HeETH ZürichVerified email at inf.ethz.ch
