| Deep gaussian process for crop yield prediction based on remote sensing data J You, X Li, M Low, D Lobell, S Ermon Proceedings of the AAAI conference on artificial intelligence 31 (1), 2017 | 655 | 2017 |
| Optimizing chemical reactions with deep reinforcement learning Z Zhou, X Li, RN Zare ACS central science 3 (12), 1337-1344, 2017 | 539 | 2017 |
| Recurrent autoregressive networks for online multi-object tracking K Fang, Y Xiang, X Li, S Savarese 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), 466-475, 2018 | 331 | 2018 |
| Online linear programming: Dual convergence, new algorithms, and regret bounds X Li, Y Ye Operations Research 70 (5), 2948-2966, 2022 | 69 | 2022 |
| Online stochastic optimization with wasserstein based non-stationarity J Jiang, X Li, J Zhang arXiv preprint arXiv:2012.06961, 2020 | 42 | 2020 |
| 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 | 41 | 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 | 33* | 2021 |
| Graph convolution: A high-order and adaptive approach Z Zhou, X Li arXiv preprint arXiv:1706.09916, 2017 | 30 | 2017 |
| Non-stationary bandits with knapsacks S Liu, J Jiang, X Li Advances in Neural Information Processing Systems 35, 16522-16532, 2022 | 29 | 2022 |
| Dynamic pricing with external information and inventory constraint X Li, Z Zheng Management Science 70 (9), 5985-6001, 2024 | 23 | 2024 |
| Quantile Markov decision processes X Li, H Zhong, ML Brandeau Operations research 70 (3), 1428-1447, 2022 | 23* | 2022 |
| Demand prediction, predictive shipping, and product allocation for large-scale e-commerce X Li, Y Zheng, Z Zhou, Z Zheng Predictive Shipping, and Product Allocation for Large-Scale E-Commerce …, 2019 | 19 | 2019 |
| Hierarchical modeling of seed variety yields and decision making for future planting plans H Zhong, X Li, D Lobell, S Ermon, ML Brandeau Environment Systems and Decisions 38, 458-470, 2018 | 19 | 2018 |
| Uncertainty estimation and quantification for llms: A simple supervised approach L Liu, Y Pan, X Li, G Chen arXiv preprint arXiv:2404.15993, 2024 | 18 | 2024 |
| On dynamic pricing with covariates H Wang, K Talluri, X Li Operations Research, 2025 | 16 | 2025 |
| A closed-form expansion approach for pricing discretely monitored variance swaps C Li, X Li Operations Research Letters 43 (4), 450-455, 2015 | 16 | 2015 |
| An improved analysis of LP-based control for revenue management G Chen, X Li, Y Ye Operations Research 72 (3), 1124-1138, 2024 | 15 | 2024 |
| Predict-then-calibrate: A new perspective of robust contextual lp C Sun, L Liu, X Li Advances in Neural Information Processing Systems 36, 17713-17741, 2023 | 14 | 2023 |
| Data-driven ranking and selection: High-dimensional covariates and general dependence X Li, X Zhang, Z Zheng 2018 Winter Simulation Conference (WSC), 1933-1944, 2018 | 14 | 2018 |
| 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 | 12 | 2023 |
