Optimizing curbside parking resources subject to congestion constraints. - Chase Dowling; Tanner Fiez; Lillian J. Ratliff; Baosen Zhang (CDC, 2017)

Gradient-based inverse risk-sensitive reinforcement learning. - Eric Mazumdar; Lillian J. Ratliff; Tanner Fiez; S. Shankar Sastry (CDC, 2017)

How Much Urban Traffic is Searching for Parking? - Chase Dowling; Tanner Fiez; Lillian J. Ratliff; Baosen Zhang (CoRR, 2017)

Data Driven Spatio-Temporal Modeling of Parking Demand. - Tanner Fiez; Lillian J. Ratliff; Chase Dowling; Baosen Zhang (ACC, 2018)

Combinatorial Bandits for Incentivizing Agents with Dynamic Preferences. - Tanner Fiez; Shreyas Sekar; Liyuan Zheng; Lillian J. Ratliff (UAI, 2018)

Incentives in the Dark: Multi-armed Bandits for Evolving Users with Unknown Type. - Lillian J. Ratliff; Shreyas Sekar; Liyuan Zheng; Tanner Fiez (CoRR, 2018)

Sequential Experimental Design for Transductive Linear Bandits. - Tanner Fiez; Lalit Jain; Kevin G. Jamieson; Lillian J. Ratliff (NeurIPS, 2019)

A Perspective on Incentive Design: Challenges and Opportunities. - Lillian J. Ratliff; Roy Dong; Shreyas Sekar; Tanner Fiez (Annu. Rev. Control. Robotics Auton. Syst., 2019)

Convergence of Learning Dynamics in Stackelberg Games. - Tanner Fiez; Benjamin Chasnov; Lillian J. Ratliff (CoRR, 2019)

Implicit Learning Dynamics in Stackelberg Games: Equilibria Characterization, Convergence Analysis, and Empirical Study. - Tanner Fiez; Benjamin Chasnov; Lillian J. Ratliff (ICML, 2020)

A SUPER* Algorithm to Optimize Paper Bidding in Peer Review. - Tanner Fiez; Nihar B. Shah; Lillian J. Ratliff (UAI, 2020)

A SUPER* Algorithm to Optimize Paper Bidding in Peer Review. - Tanner Fiez; Nihar B. Shah; Lillian J. Ratliff (CoRR, 2020)

Gradient Descent-Ascent Provably Converges to Strict Local Minmax Equilibria with a Finite Timescale Separation. - Tanner Fiez; Lillian J. Ratliff (CoRR, 2020)

Gaussian Mixture Models for Parking Demand Data. - Tanner Fiez; Lillian J. Ratliff (IEEE Trans. Intell. Transp. Syst., 2020)

Evolutionary Game Theory Squared: Evolving Agents in Endogenously Evolving Zero-Sum Games. - Stratis Skoulakis; Tanner Fiez; Ryann Sim; Georgios Piliouras; Lillian J. Ratliff (AAAI, 2021)

Local Convergence Analysis of Gradient Descent Ascent with Finite Timescale Separation. - Tanner Fiez; Lillian J. Ratliff (ICLR, 2021)

Global Convergence to Local Minmax Equilibrium in Classes of Nonconvex Zero-Sum Games. - Tanner Fiez; Lillian J. Ratliff; Eric Mazumdar; Evan Faulkner; Adhyyan Narang (NeurIPS, 2021)

Online Learning in Periodic Zero-Sum Games. - Tanner Fiez; Ryann Sim; Stratis Skoulakis; Georgios Piliouras; Lillian J. Ratliff (NeurIPS, 2021)

Adaptive Incentive Design. - Lillian J. Ratliff; Tanner Fiez (IEEE Trans. Autom. Control., 2021)

Stackelberg Actor-Critic: Game-Theoretic Reinforcement Learning Algorithms. - Liyuan Zheng; Tanner Fiez; Zane Alumbaugh; Benjamin Chasnov; Lillian J. Ratliff (AAAI, 2022)

Minimax Optimization with Smooth Algorithmic Adversaries. - Tanner Fiez; Chi Jin 001; Praneeth Netrapalli; Lillian J. Ratliff (ICLR, 2022)

Adaptive Experimental Design and Counterfactual Inference. - Tanner Fiez; Sergio Gamez; Arick Chen; Houssam Nassif; Lalit Jain (CoRR, 2022)

Neural Insights for Digital Marketing Content Design. - Fanjie Kong; Yuan Li 031; Houssam Nassif; Tanner Fiez; Ricardo Henao; Shreya Chakrabarti (KDD, 2023)

Experimental Designs for Heteroskedastic Variance. - Justin Weltz; Tanner Fiez; Alexander Volfovsky; Eric Laber; Blake Mason; Houssam Nassif; Lalit Jain (NeurIPS, 2023)

Adaptive Experimentation When You Can't Experiment. - Yao Zhao; Kwang-Sung Jun; Tanner Fiez; Lalit Jain (NeurIPS, 2024)

Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice. - Tanner Fiez; Houssam Nassif; Yu-Cheng Chen; Sergio Gamez; Lalit Jain (WWW, 2024)

Segment Discovery: Enhancing E-commerce Targeting. - Qiqi Li; Roopali Singh; Charin Polpanumas; Tanner Fiez; Namita Kumar; Shreya Chakrabarti (CoRR, 2024)

Multi-Metric Adaptive Experimental Design under Fixed Budget with Validation. - Qining Zhang; Tanner Fiez; Yi Liu; Wenyang Liu (CoRR, 2025)