Tanner Fiez - RankMe

38 papers A* 12A 2C 1Journal 21Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Multi-Metric Adaptive Experimental Design under Fixed Budget with Validation. CoRR Qining Zhang, Tanner Fiez, Yi Liu, Wenyang Liu
2024	A*	`conf`	Adaptive Experimentation When You Can't Experiment. NeurIPS Yao Zhao, Kwang-Sung Jun, Tanner Fiez, Lalit Jain
2024	J	`jnl`	Adaptive Experimentation When You Can't Experiment. CoRR Yao Zhao, Kwang-Sung Jun, Tanner Fiez, Lalit Jain
2024	A*	`conf`	Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice. WWW Tanner Fiez, Houssam Nassif, Yu-Cheng Chen, Sergio Gamez, Lalit Jain
2024	J	`jnl`	Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice. CoRR Tanner Fiez, Houssam Nassif, Yu-Cheng Chen, Sergio Gamez, Lalit Jain
2024	J	`jnl`	Segment Discovery: Enhancing E-commerce Targeting. CoRR Qiqi Li, Roopali Singh, Charin Polpanumas, Tanner Fiez, Namita Kumar, Shreya Chakrabarti
2023	A*	`conf`	Experimental Designs for Heteroskedastic Variance. NeurIPS Justin Weltz, Tanner Fiez, Alexander Volfovsky, Eric Laber, Blake Mason, Houssam Nassif, Lalit Jain
2023	A*	`conf`	Neural Insights for Digital Marketing Content Design. KDD Fanjie Kong, Yuan Li, Houssam Nassif, Tanner Fiez, Ricardo Henao, Shreya Chakrabarti
2023	J	`jnl`	Neural Insights for Digital Marketing Content Design. CoRR Fanjie Kong, Yuan Li, Tanner Fiez, Shreya Chakrabarti, Ricardo Henao, Houssam Nassif
2022	J	`jnl`	Adaptive Experimental Design and Counterfactual Inference. CoRR Tanner Fiez, Sergio Gamez, Arick Chen, Houssam Nassif, Lalit Jain
2022	A*	`conf`	Minimax Optimization with Smooth Algorithmic Adversaries. ICLR Tanner Fiez, Chi Jin, Praneeth Netrapalli, Lillian J. Ratliff
2022	A*	`conf`	Stackelberg Actor-Critic: Game-Theoretic Reinforcement Learning Algorithms. AAAI Liyuan Zheng, Tanner Fiez, Zane Alumbaugh, Benjamin Chasnov, Lillian J. Ratliff
2021	J	`jnl`	Adaptive Incentive Design. IEEE Trans. Autom. Control. Lillian J. Ratliff, Tanner Fiez
2021	A*	`conf`	Evolutionary Game Theory Squared: Evolving Agents in Endogenously Evolving Zero-Sum Games. AAAI Stratis Skoulakis, Tanner Fiez, Ryann Sim, Georgios Piliouras, Lillian J. Ratliff
2021	A*	`conf`	Global Convergence to Local Minmax Equilibrium in Classes of Nonconvex Zero-Sum Games. NeurIPS Tanner Fiez, Lillian J. Ratliff, Eric Mazumdar, Evan Faulkner, Adhyyan Narang
2021	A*	`conf`	Local Convergence Analysis of Gradient Descent Ascent with Finite Timescale Separation. ICLR Tanner Fiez, Lillian J. Ratliff
2021	J	`jnl`	Minimax Optimization with Smooth Algorithmic Adversaries. CoRR Tanner Fiez, Chi Jin, Praneeth Netrapalli, Lillian J. Ratliff
2021	A*	`conf`	Online Learning in Periodic Zero-Sum Games. NeurIPS Tanner Fiez, Ryann Sim, Stratis Skoulakis, Georgios Piliouras, Lillian J. Ratliff
2021	J	`jnl`	Online Learning in Periodic Zero-Sum Games. CoRR Tanner Fiez, Ryann Sim, Stratis Skoulakis, Georgios Piliouras, Lillian J. Ratliff
2021	J	`jnl`	Stackelberg Actor-Critic: Game-Theoretic Reinforcement Learning Algorithms. CoRR Liyuan Zheng, Tanner Fiez, Zane Alumbaugh, Benjamin Chasnov, Lillian J. Ratliff
2020	J	`jnl`	A SUPER CoRR Tanner Fiez, Nihar B. Shah, Lillian J. Ratliff
2020	A	`conf`	A SUPER* Algorithm to Optimize Paper Bidding in Peer Review. UAI Tanner Fiez, Nihar B. Shah, Lillian J. Ratliff
2020	J	`jnl`	Evolutionary Game Theory Squared: Evolving Agents in Endogenously Evolving Zero-Sum Games. CoRR Stratis Skoulakis, Tanner Fiez, Ryann Sim, Georgios Piliouras, Lillian J. Ratliff
2020	J	`jnl`	Gaussian Mixture Models for Parking Demand Data. IEEE Trans. Intell. Transp. Syst. Tanner Fiez, Lillian J. Ratliff
2020	J	`jnl`	Gradient Descent-Ascent Provably Converges to Strict Local Minmax Equilibria with a Finite Timescale Separation. CoRR Tanner Fiez, Lillian J. Ratliff
2020	A*	`conf`	Implicit Learning Dynamics in Stackelberg Games: Equilibria Characterization, Convergence Analysis, and Empirical Study. ICML Tanner Fiez, Benjamin Chasnov, Lillian J. Ratliff
2019	J	`jnl`	A Perspective on Incentive Design: Challenges and Opportunities. Annu. Rev. Control. Robotics Auton. Syst. Lillian J. Ratliff, Roy Dong, Shreyas Sekar, Tanner Fiez
2019	J	`jnl`	Convergence of Learning Dynamics in Stackelberg Games. CoRR Tanner Fiez, Benjamin Chasnov, Lillian J. Ratliff
2019	A*	`conf`	Sequential Experimental Design for Transductive Linear Bandits. NeurIPS Tanner Fiez, Lalit Jain, Kevin Jamieson, Lillian J. Ratliff
2019	J	`jnl`	Sequential Experimental Design for Transductive Linear Bandits. CoRR Tanner Fiez, Lalit Jain, Kevin Jamieson, Lillian J. Ratliff
2018	J	`jnl`	Adaptive Incentive Design. CoRR Lillian J. Ratliff, Tanner Fiez
2018	A	`conf`	Combinatorial Bandits for Incentivizing Agents with Dynamic Preferences. UAI Tanner Fiez, Shreyas Sekar, Liyuan Zheng, Lillian J. Ratliff
2018	J	`jnl`	Combinatorial Bandits for Incentivizing Agents with Dynamic Preferences. CoRR Tanner Fiez, Shreyas Sekar, Liyuan Zheng, Lillian J. Ratliff
2018	C	`conf`	Data Driven Spatio-Temporal Modeling of Parking Demand. ACC Tanner Fiez, Lillian J. Ratliff, Chase Dowling, Baosen Zhang
2018	J	`jnl`	Incentives in the Dark: Multi-armed Bandits for Evolving Users with Unknown Type. CoRR Lillian J. Ratliff, Shreyas Sekar, Liyuan Zheng, Tanner Fiez
2017	—	`conf`	Gradient-based inverse risk-sensitive reinforcement learning. CDC Eric Mazumdar, Lillian J. Ratliff, Tanner Fiez, S. Shankar Sastry
2017	J	`jnl`	How Much Urban Traffic is Searching for Parking? CoRR Chase Dowling, Tanner Fiez, Lillian J. Ratliff, Baosen Zhang
2017	—	`conf`	Optimizing curbside parking resources subject to congestion constraints. CDC Chase Dowling, Tanner Fiez, Lillian J. Ratliff, Baosen Zhang