| Provably Convergent Schrodinger Bridge with Applications to Probabilistic Time Series Imputation Y Chen, W Deng, S Fang, F Li, NT Yang, Y Zhang, K Rasul, S Zhe, ... International Conference on Machine Learning 202 (PMLR), 2023 | 31 | 2023 |
| Unbiased simulation for optimizing stochastic function compositions J Blanchet, D Goldfarb, G Iyengar, F Li, C Zhou arXiv preprint arXiv:1711.07564, 2017 | 27 | 2017 |
| Robust importance weighting for covariate shift F Li, H Lam, S Prusty International Conference on Artificial Intelligence and Statistics (AISTATS …, 2020 | 17 | 2020 |
| Accelerated policy evaluation: Learning adversarial environments with adaptive importance sampling M Xu, P Huang, F Li, J Zhu, X Qi, K Oguchi, Z Huang, H Lam, D Zhao arXiv preprint arXiv:2106.10566 1 (4), 2021 | 15 | 2021 |
| Sampling uncertain constraints under parametric distributions H Lam, F Li 2018 Winter Simulation Conference (WSC), 2072-2083, 2018 | 6 | 2018 |
| Risk bounds on aleatoric uncertainty recovery Y Zhang, J Lin, F Li, Y Adler, K Rasul, A Schneider, Y Nevmyvaka International Conference on Artificial Intelligence and Statistics, 6015-6036, 2023 | 5 | 2023 |
| Scalable Safety-Critical Policy Evaluation with Accelerated Rare Event Sampling M Xu, P Huang, F Li, J Zhu, X Qi, K Oguchi, Z Huang, H Lam, D Zhao 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022 | 4 | 2022 |
| General Feasibility Bounds for Sample Average Approximation via Vapnik-Chervonenkis Dimension H Lam, F Li SIAM Journal on Optimization 32 (2), 1471-1497, 2021 | 4 | 2021 |
| Information theoretic clustering via divergence maximization among clusters S Garg, M Dalirrooyfard, A Schneider, Y Adler, Y Nevmyvaka, Y Chen, ... Uncertainty in Artificial Intelligence, 624-634, 2023 | 2 | 2023 |
| Parametric scenario optimization under limited data: A distributionally robust optimization view H Lam, F Li ACM Transactions on Modeling and Computer Simulation (TOMACS) 30 (4), 1-41, 2020 | 2 | 2020 |
| Constrained reinforcement learning via policy splitting H Chen, H Lam, F Li, A Meisami Asian Conference on Machine Learning, 209-224, 2020 | 2 | 2020 |
| Do price trajectory data increase the efficiency of market impact estimation? F Li, V Ihnatiuk, R Kinnear, A Schneider, Y Nevmyvaka Quantitative Finance, 2024 | 1 | 2024 |
| Unbiased sampling of multidimensional partial differential equations with random coefficients J Blanchet, F Li, X Li arXiv preprint arXiv:1806.03362, 2018 | 1 | 2018 |
| Reweighting Improves Conditional Risk Bounds Y Zhang, J Lin, F Li, S Zheng, A Raj, A Schneider, Y Nevmyvaka arXiv preprint arXiv:2501.02353, 2025 | | 2025 |
| Prediction-Enhanced Monte Carlo: A Machine Learning View on Control Variate F Li, H Chen, J Lin, A Gupta, X Tan, G Xu, Y Nevmyvaka, A Capponi, ... arXiv preprint arXiv:2412.11257, 2024 | | 2024 |
| A Communication-Efficient Algorithm for Federated Multilevel Stochastic Compositional Optimization S Yang, F Li IEEE Transactions on Signal Processing, 2024 | | 2024 |
| Detection of short-term temporal dependencies in hawkes processes with heterogeneous background dynamics Y Chen, F Li, A Schneider, Y Nevmyvaka, A Amarasingham, H Lam Uncertainty in Artificial Intelligence, 369-380, 2023 | | 2023 |
| Stochastic Methods in Optimization and Machine Learning F Li Columbia University, 2021 | | 2021 |
