Simple and fast algorithm for binary integer and online linear programming X Li, C Sun, Y Ye Advances in Neural Information Processing Systems 33, 9412-9421, 2020 | 25 | 2020 |
The symmetry between arms and knapsacks: A primal-dual approach for bandits with knapsacks X Li, C Sun, Y Ye International Conference on Machine Learning, 6483-6492, 2021 | 24* | 2021 |
Solving Linear Programs with Fast Online Learning Algorithms W Gao, D Ge, C Sun, Y Ye | 5* | 2023 |
Predict-then-calibrate: A new perspective of robust contextual LP C Sun, L Liu, X Li Advances in Neural Information Processing Systems 36, 2024 | 4 | 2024 |
Learning to make adherence-aware advice G Chen, X Li, C Sun, H Wang arXiv preprint arXiv:2310.00817, 2023 | 4 | 2023 |
Maximum optimality margin: A unified approach for contextual linear programming and inverse linear programming C Sun, S Liu, X Li International Conference on Machine Learning, 32886-32912, 2023 | 4 | 2023 |
Simple and fast algorithm for binary integer and online linear programming X Li, C Sun, Y Ye Mathematical Programming 200 (2), 831-875, 2023 | 3 | 2023 |
Learning from stochastically revealed preference J Birge, X Li, C Sun Advances in Neural Information Processing Systems 35, 35061-35071, 2022 | 3 | 2022 |
An Adaptive State Aggregation Algorithm for Markov Decision Processes G Chen, JD Gaebler, M Peng, C Sun, Y Ye arXiv preprint arXiv:2107.11053, 2021 | 3 | 2021 |
When No-Rejection Learning is Optimal for Regression with Rejection X Li, S Liu, C Sun, H Wang arXiv preprint arXiv:2307.02932, 2023 | 2 | 2023 |
Stochastic inverse optimization JR Birge, X Li, C Sun Working paper, 2022 | 2 | 2022 |
When No-Rejection Learning is Consistent for Regression with Rejection X Li, S Liu, C Sun, H Wang International Conference on Artificial Intelligence and Statistics, 1126-1134, 2024 | | 2024 |
Decoupling Learning and Decision-Making: Breaking the Barrier in Online Resource Allocation with First-Order Methods W Gao, C Sun, C Xue, D Ge, Y Ye arXiv preprint arXiv:2402.07108, 2024 | | 2024 |