| Implicit learning dynamics in stackelberg games: Equilibria characterization, convergence analysis, and empirical study T Fiez, B Chasnov, L Ratliff International Conference on Machine Learning, 3133-3144, 2020 | 207* | 2020 |
| Sequential experimental design for transductive linear bandits T Fiez, L Jain, KG Jamieson, L Ratliff Advances in neural information processing systems 32, 2019 | 123 | 2019 |
| Local convergence analysis of gradient descent ascent with finite timescale separation T Fiez, LJ Ratliff Proceedings of the International Conference on Learning Representation, 2021 | 55* | 2021 |
| A perspective on incentive design: Challenges and opportunities LJ Ratliff, R Dong, S Sekar, T Fiez Annual Review of Control, Robotics, and Autonomous Systems 2, 305-338, 2019 | 53 | 2019 |
| A SUPER* algorithm to optimize paper bidding in peer review T Fiez, N Shah, L Ratliff Conference on Uncertainty in Artificial Intelligence, 580-589, 2020 | 51 | 2020 |
| How much urban traffic is searching for parking C Dowling, T Fiez, L Ratliff, B Zhang arXiv preprint arXiv:1702.06156, 1-20, 2017 | 49* | 2017 |
| Stackelberg actor-critic: Game-theoretic reinforcement learning algorithms L Zheng, T Fiez, Z Alumbaugh, B Chasnov, LJ Ratliff AAAI Conference on Artificial Intelligence, 2021 | 40 | 2021 |
| Adaptive incentive design LJ Ratliff, T Fiez IEEE Transactions on Automatic Control 66 (8), 3871-3878, 2020 | 39 | 2020 |
| Global convergence to local minmax equilibrium in classes of nonconvex zero-sum games T Fiez, L Ratliff, E Mazumdar, E Faulkner, A Narang Advances in Neural Information Processing Systems 34, 29049-29063, 2021 | 24 | 2021 |
| Gaussian mixture models for parking demand data T Fiez, LJ Ratliff IEEE Transactions on Intelligent Transportation Systems 21 (8), 3571-3580, 2019 | 23* | 2019 |
| Gradient-based inverse risk-sensitive reinforcement learning E Mazumdar, LJ Ratliff, T Fiez, SS Sastry 2017 IEEE 56th Annual Conference on Decision and Control (CDC), 5796-5801, 2017 | 22* | 2017 |
| Data driven spatio-temporal modeling of parking demand T Fiez, LJ Ratliff, C Dowling, B Zhang 2018 Annual American Control Conference (ACC), 2757-2762, 2018 | 21 | 2018 |
| Evolutionary game theory squared: Evolving agents in endogenously evolving zero-sum games S Skoulakis, T Fiez, R Sim, G Piliouras, L Ratliff Proceedings of the AAAI Conference on Artificial Intelligence 35 (13), 11343 …, 2021 | 15 | 2021 |
| Optimizing curbside parking resources subject to congestion constraints C Dowling, T Fiez, L Ratliff, B Zhang 2017 IEEE 56th Annual Conference on Decision and Control (CDC), 5080-5085, 2017 | 15 | 2017 |
| Neural insights for digital marketing content design F Kong, Y Li, H Nassif, T Fiez, R Henao, S Chakrabarti Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 9 | 2023 |
| Minimax optimization with smooth algorithmic adversaries T Fiez, C Jin, P Netrapalli, LJ Ratliff International Conference on Learning Learning Representations, 2021 | 9 | 2021 |
| Multi-armed bandits for correlated markovian environments with smoothed reward feedback T Fiez, S Sekar, LJ Ratliff arXiv preprint arXiv:1803.04008, 2018 | 8 | 2018 |
| Adaptive experimental design and counterfactual inference T Fiez, S Gamez, A Chen, H Nassif, L Jain RecSys Consequences Workshop, 2022 | 7 | 2022 |
| Online learning in periodic zero-sum games T Fiez, R Sim, S Skoulakis, G Piliouras, L Ratliff Advances in Neural Information Processing Systems 34, 10313-10325, 2021 | 7 | 2021 |
| Stackelberg actor-critic: A game-theoretic perspective L Zheng, T Fiez, Z Alumbaugh, B Chasnov, LJ Ratliff AAAI Workshop on Reinforcement Learning and Games, 2021 | 7 | 2021 |
Lillian J. RatliffAssociate Professor, University of Washington在 uw.edu 的电子邮件经过验证
