Tanner Fiez

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 35

Top Topics

Convergence Analysis

Evolutionary Game

Experimental Designs

Reinforcement Learning

Top Venues

Publications

Tanner Fiez, Houssam Nassif, Arick Chen, Sergio Gamez, Lalit Jain
Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice. CoRR (2024)
Yao Zhao, Kwang-Sung Jun, Tanner Fiez, Lalit Jain
Adaptive Experimentation When You Can't Experiment. CoRR (2024)
Tanner Fiez, Houssam Nassif, Yu-Cheng Chen, Sergio Gamez, Lalit Jain
Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice. WWW (2024)
Fanjie Kong, Yuan Li, Houssam Nassif, Tanner Fiez, Ricardo Henao, Shreya Chakrabarti
Neural Insights for Digital Marketing Content Design. KDD (2023)
Fanjie Kong, Yuan Li, Houssam Nassif, Tanner Fiez, Shreya Chakrabarti, Ricardo Henao
Neural Insights for Digital Marketing Content Design. CoRR (2023)
Justin Weltz, Tanner Fiez, Alexander Volfovsky, Eric Laber, Blake Mason, Houssam Nassif, Lalit Jain
Experimental Designs for Heteroskedastic Variance. NeurIPS (2023)
Tanner Fiez, Sergio Gamez, Arick Chen, Houssam Nassif, Lalit Jain
Adaptive Experimental Design and Counterfactual Inference. CoRR (2022)
Liyuan Zheng, Tanner Fiez, Zane Alumbaugh, Benjamin Chasnov, Lillian J. Ratliff
Stackelberg Actor-Critic: Game-Theoretic Reinforcement Learning Algorithms. AAAI (2022)
Tanner Fiez, Chi Jin, Praneeth Netrapalli, Lillian J. Ratliff
Minimax Optimization with Smooth Algorithmic Adversaries. ICLR (2022)
Stratis Skoulakis, Tanner Fiez, Ryann Sim, Georgios Piliouras, Lillian J. Ratliff
Evolutionary Game Theory Squared: Evolving Agents in Endogenously Evolving Zero-Sum Games. AAAI (2021)
Tanner Fiez, Ryann Sim, Stratis Skoulakis, Georgios Piliouras, Lillian J. Ratliff
Online Learning in Periodic Zero-Sum Games. CoRR (2021)
Tanner Fiez, Lillian J. Ratliff
Local Convergence Analysis of Gradient Descent Ascent with Finite Timescale Separation. ICLR (2021)
Tanner Fiez, Chi Jin, Praneeth Netrapalli, Lillian J. Ratliff
Minimax Optimization with Smooth Algorithmic Adversaries. CoRR (2021)
Tanner Fiez, Ryann Sim, Stratis Skoulakis, Georgios Piliouras, Lillian J. Ratliff
Online Learning in Periodic Zero-Sum Games. NeurIPS (2021)
Tanner Fiez, Lillian J. Ratliff, Eric Mazumdar, Evan Faulkner, Adhyyan Narang
Global Convergence to Local Minmax Equilibrium in Classes of Nonconvex Zero-Sum Games. NeurIPS (2021)
Liyuan Zheng, Tanner Fiez, Zane Alumbaugh, Benjamin Chasnov, Lillian J. Ratliff
Stackelberg Actor-Critic: Game-Theoretic Reinforcement Learning Algorithms. CoRR (2021)
Lillian J. Ratliff, Tanner Fiez
Adaptive Incentive Design. IEEE Trans. Autom. Control. 66 (8) (2021)
Stratis Skoulakis, Tanner Fiez, Ryann Sim, Georgios Piliouras, Lillian J. Ratliff
Evolutionary Game Theory Squared: Evolving Agents in Endogenously Evolving Zero-Sum Games. CoRR (2020)
Tanner Fiez, Benjamin Chasnov, Lillian J. Ratliff
Implicit Learning Dynamics in Stackelberg Games: Equilibria Characterization, Convergence Analysis, and Empirical Study. ICML (2020)
Tanner Fiez, Lillian J. Ratliff
Gradient Descent-Ascent Provably Converges to Strict Local Minmax Equilibria with a Finite Timescale Separation. CoRR (2020)
Tanner Fiez, Lillian J. Ratliff
Gaussian Mixture Models for Parking Demand Data. IEEE Trans. Intell. Transp. Syst. 21 (8) (2020)
Tanner Fiez, Nihar B. Shah, Lillian J. Ratliff
Algorithm to Optimize Paper Bidding in Peer Review. CoRR (2020)
Tanner Fiez, Nihar B. Shah, Lillian J. Ratliff
A SUPER* Algorithm to Optimize Paper Bidding in Peer Review. UAI (2020)
Tanner Fiez, Benjamin Chasnov, Lillian J. Ratliff
Convergence of Learning Dynamics in Stackelberg Games. CoRR (2019)
Lillian J. Ratliff, Roy Dong, Shreyas Sekar, Tanner Fiez
A Perspective on Incentive Design: Challenges and Opportunities. Annu. Rev. Control. Robotics Auton. Syst. 2 (2019)
Tanner Fiez, Lalit Jain, Kevin G. Jamieson, Lillian J. Ratliff
Sequential Experimental Design for Transductive Linear Bandits. CoRR (2019)
Tanner Fiez, Lalit Jain, Kevin G. Jamieson, Lillian J. Ratliff
Sequential Experimental Design for Transductive Linear Bandits. NeurIPS (2019)
Tanner Fiez, Shreyas Sekar, Liyuan Zheng, Lillian J. Ratliff
Combinatorial Bandits for Incentivizing Agents with Dynamic Preferences. UAI (2018)
Lillian J. Ratliff, Shreyas Sekar, Liyuan Zheng, Tanner Fiez
Incentives in the Dark: Multi-armed Bandits for Evolving Users with Unknown Type. CoRR (2018)
Tanner Fiez, Shreyas Sekar, Liyuan Zheng, Lillian J. Ratliff
Combinatorial Bandits for Incentivizing Agents with Dynamic Preferences. CoRR (2018)
Lillian J. Ratliff, Tanner Fiez
Adaptive Incentive Design. CoRR (2018)
Tanner Fiez, Lillian J. Ratliff, Chase Dowling, Baosen Zhang
Data Driven Spatio-Temporal Modeling of Parking Demand. ACC (2018)
Eric Mazumdar, Lillian J. Ratliff, Tanner Fiez, S. Shankar Sastry
Gradient-based inverse risk-sensitive reinforcement learning. CDC (2017)
Chase Dowling, Tanner Fiez, Lillian J. Ratliff, Baosen Zhang
How Much Urban Traffic is Searching for Parking? CoRR (2017)
Chase Dowling, Tanner Fiez, Lillian J. Ratliff, Baosen Zhang
Optimizing curbside parking resources subject to congestion constraints. CDC (2017)