The curious case of adversarially robust models: More data can help, double descend, or hurt generalization Y Min, L Chen, A Karbasi Uncertainty in Artificial Intelligence, 129-139, 2021 | 71 | 2021 |
Multiple descent: Design your own generalization curve L Chen, Y Min, M Belkin, A Karbasi Advances in Neural Information Processing Systems 34, 8898-8912, 2021 | 68 | 2021 |
More data can expand the generalization gap between adversarially robust and standard models L Chen, Y Min, M Zhang, A Karbasi International Conference on Machine Learning, 1670-1680, 2020 | 66 | 2020 |
Bootstrapping semi-supervised medical image segmentation with anatomical-aware contrastive distillation C You, W Dai, Y Min, L Staib, JS Duncan International conference on information processing in medical imaging, 641-653, 2023 | 44 | 2023 |
Variance-aware off-policy evaluation with linear function approximation Y Min, T Wang, D Zhou, Q Gu Advances in neural information processing systems 34, 7598-7610, 2021 | 36 | 2021 |
Mine your own anatomy: Revisiting medical image segmentation with extremely limited labels C You, W Dai, F Liu, Y Min, H Su, X Zhang, X Li, DA Clifton, L Staib, ... arXiv preprint arXiv:2209.13476, 2022 | 34 | 2022 |
Rethinking semi-supervised medical image segmentation: A variance-reduction perspective C You, W Dai, Y Min, F Liu, D Clifton, SK Zhou, L Staib, J Duncan Advances in Neural Information Processing Systems 36, 2024 | 30 | 2024 |
Learning stochastic shortest path with linear function approximation Y Min, J He, T Wang, Q Gu International Conference on Machine Learning, 15584-15629, 2022 | 30 | 2022 |
A simple and provably efficient algorithm for asynchronous federated contextual linear bandits J He, T Wang, Y Min, Q Gu Advances in neural information processing systems 35, 4762-4775, 2022 | 28 | 2022 |
Pessimism in the face of confounders: Provably efficient offline reinforcement learning in partially observable markov decision processes M Lu, Y Min, Z Wang, Z Yang arXiv preprint arXiv:2205.13589, 2022 | 22 | 2022 |
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 | 20 | 2022 |
Implicit anatomical rendering for medical image segmentation with stochastic experts C You, W Dai, Y Min, L Staib, JS Duncan International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 14 | 2023 |
Action++: improving semi-supervised medical image segmentation with adaptive anatomical contrast C You, W Dai, Y Min, L Staib, J Sekhon, JS Duncan International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 12 | 2023 |
Cooperative multi-agent reinforcement learning: Asynchronous communication and linear function approximation Y Min, J He, T Wang, Q Gu International Conference on Machine Learning, 24785-24811, 2023 | 5 | 2023 |
Discontinuous growth of DNA plectonemes due to atomic scale friction Y Min, PK Purohit Soft matter 14 (37), 7759-7770, 2018 | 5 | 2018 |
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 | 4 | 2023 |
Noise-Adaptive Thompson Sampling for Linear Contextual Bandits R Xu, Y Min, T Wang Advances in Neural Information Processing Systems 36, 2024 | 1 | 2024 |
Multi-agent reinforcement learning: Asynchronous communication and linear function approximation Y Min, J He, T Wang, Q Gu arXiv preprint arXiv:2305.06446, 2023 | 1 | 2023 |
Calibrating Multi-modal Representations: A Pursuit of Group Robustness without Annotations C You, Y Min, W Dai, JS Sekhon, L Staib, JS Duncan arXiv preprint arXiv:2403.07241, 2024 | | 2024 |