| Bail: Best-action imitation learning for batch deep reinforcement learning X Chen, Z Zhou, Z Wang, C Wang, Y Wu, K Ross Advances in Neural Information Processing Systems 33, 18353-18363, 2020 | 103 | 2020 |
| Striving for simplicity and performance in off-policy DRL: Output normalization and non-uniform sampling C Wang, Y Wu, Q Vuong, K Ross International Conference on Machine Learning, 10070-10080, 2020 | 35 | 2020 |
| You can yak but you can't hide: Localizing anonymous social network users M Xue, C Ballard, K Liu, C Nemelka, Y Wu, K Ross, H Qian Proceedings of the 2016 Internet Measurement Conference, 25-31, 2016 | 26 | 2016 |
| Aggressive q-learning with ensembles: Achieving both high sample efficiency and high asymptotic performance Y Wu, X Chen, C Wang, Y Zhang, KW Ross arXiv preprint arXiv:2111.09159, 2021 | 7 | 2021 |
| Taking the Pulse of US college campuses with location-based anonymous mobile apps Y Wu, T Minkus, KW Ross ACM Transactions on Intelligent Systems and Technology (TIST) 9 (1), 1-18, 2017 | 5 | 2017 |
| Towards simplicity in deep reinforcement learning: Streamlined off-policy learning C Wang, Y Wu, Q Vuong, K Ross | 4 | 2019 |
| Spatio-temporal Incentives Optimization for Ride-hailing Services with Offline Deep Reinforcement Learning Y Wu, Q Li, Z Qin arXiv preprint arXiv:2211.03240, 2022 | 3 | 2022 |
| Radio Signal Classification by Adversarially Robust Quantum Machine Learning Y Wu, E Adermann, C Thapa, S Camtepe, H Suzuki, M Usman arXiv preprint arXiv:2312.07821, 2023 | 1 | 2023 |
