Seuraa
Tanner Fiez
Tanner Fiez
Applied Scientist at Amazon
Vahvistettu sähköpostiosoite verkkotunnuksessa amazon.com
Nimike
Viittaukset
Viittaukset
Vuosi
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
222*2020
Sequential experimental design for transductive linear bandits
T Fiez, L Jain, KG Jamieson, L Ratliff
Advances in neural information processing systems 32, 2019
1432019
Local convergence analysis of gradient descent ascent with finite timescale separation
T Fiez, LJ Ratliff
Proceedings of the International Conference on Learning Representation, 2021
60*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
572019
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
552020
Stackelberg actor-critic: Game-theoretic reinforcement learning algorithms
L Zheng, T Fiez, Z Alumbaugh, B Chasnov, LJ Ratliff
AAAI Conference on Artificial Intelligence, 2021
522021
How much urban traffic is searching for parking
C Dowling, T Fiez, L Ratliff, B Zhang
arXiv preprint arXiv:1702.06156, 1-20, 2017
512017
Adaptive incentive design
LJ Ratliff, T Fiez
IEEE Transactions on Automatic Control 66 (8), 3871-3878, 2020
462020
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
362021
Gaussian mixture models for parking demand data
T Fiez, LJ Ratliff
IEEE Transactions on Intelligent Transportation Systems 21 (8), 3571-3580, 2019
25*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
23*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
222018
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
182017
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
142021
Minimax optimization with smooth algorithmic adversaries
T Fiez, C Jin, P Netrapalli, LJ Ratliff
International Conference on Learning Learning Representations, 2021
122021
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
112023
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
112021
Adaptive experimental design and counterfactual inference
T Fiez, S Gamez, A Chen, H Nassif, L Jain
RecSys Consequences Workshop, 2022
102022
Multi-armed bandits for correlated markovian environments with smoothed reward feedback
T Fiez, S Sekar, LJ Ratliff
arXiv preprint arXiv:1803.04008, 2018
102018
Best of three worlds: Adaptive experimentation for digital marketing in practice
T Fiez, H Nassif, YC Chen, S Gamez, L Jain
Proceedings of the ACM Web Conference 2024, 2024
72024
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