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Tanner Fiez
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2020 – today
- 2024
- [c16]Tanner Fiez
, Houssam Nassif
Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice. WWW 2024: 3586-3597 - [i17]Tanner Fiez, Houssam Nassif, Yu-Cheng Chen, Sergio Gamez, Lalit Jain:
Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice. CoRR abs/2402.10870 (2024) - [i16]Yao Zhao, Kwang-Sung Jun, Tanner Fiez, Lalit Jain:
Adaptive Experimentation When You Can't Experiment. CoRR abs/2406.10738 (2024) - [i15]Qiqi Li, Roopali Singh, Charin Polpanumas, Tanner Fiez, Namita Kumar, Shreya Chakrabarti:
Segment Discovery: Enhancing E-commerce Targeting. CoRR abs/2409.13847 (2024) - 2023
- [c15]Fanjie Kong
Neural Insights for Digital Marketing Content Design. KDD 2023: 4320-4332 - [c14]Justin Weltz, Tanner Fiez, Alexander Volfovsky, Eric Laber, Blake Mason, Houssam Nassif, Lalit Jain:
Experimental Designs for Heteroskedastic Variance. NeurIPS 2023 - [i14]Fanjie Kong, Yuan Li, Tanner Fiez, Shreya Chakrabarti, Ricardo Henao, Houssam Nassif:
Neural Insights for Digital Marketing Content Design. CoRR abs/2302.01416 (2023) - 2022
- [c13]Liyuan Zheng, Tanner Fiez, Zane Alumbaugh, Benjamin Chasnov, Lillian J. Ratliff:
Stackelberg Actor-Critic: Game-Theoretic Reinforcement Learning Algorithms. AAAI 2022: 9217-9224 - [c12]Tanner Fiez, Chi Jin, Praneeth Netrapalli, Lillian J. Ratliff:
Minimax Optimization with Smooth Algorithmic Adversaries. ICLR 2022 - [i13]Tanner Fiez, Sergio Gamez, Arick Chen, Houssam Nassif, Lalit Jain:
Adaptive Experimental Design and Counterfactual Inference. CoRR abs/2210.14369 (2022) - 2021
- [j3]Lillian J. Ratliff
Adaptive Incentive Design. IEEE Trans. Autom. Control. 66(8): 3871-3878 (2021) - [c11]Stratis Skoulakis
Evolutionary Game Theory Squared: Evolving Agents in Endogenously Evolving Zero-Sum Games. AAAI 2021: 11343-11351 - [c10]Tanner Fiez, Lillian J. Ratliff:
Local Convergence Analysis of Gradient Descent Ascent with Finite Timescale Separation. ICLR 2021 - [c9]Tanner Fiez, Ryann Sim, Stratis Skoulakis, Georgios Piliouras, Lillian J. Ratliff:
Online Learning in Periodic Zero-Sum Games. NeurIPS 2021: 10313-10325 - [c8]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: 29049-29063 - [i12]Tanner Fiez, Chi Jin, Praneeth Netrapalli, Lillian J. Ratliff:
Minimax Optimization with Smooth Algorithmic Adversaries. CoRR abs/2106.01488 (2021) - [i11]Liyuan Zheng, Tanner Fiez, Zane Alumbaugh, Benjamin Chasnov, Lillian J. Ratliff:
Stackelberg Actor-Critic: Game-Theoretic Reinforcement Learning Algorithms. CoRR abs/2109.12286 (2021) - [i10]Tanner Fiez, Ryann Sim, Stratis Skoulakis, Georgios Piliouras, Lillian J. Ratliff:
Online Learning in Periodic Zero-Sum Games. CoRR abs/2111.03377 (2021) - 2020
- [j2]Tanner Fiez
Gaussian Mixture Models for Parking Demand Data. IEEE Trans. Intell. Transp. Syst. 21(8): 3571-3580 (2020) - [c7]Tanner Fiez, Benjamin Chasnov, Lillian J. Ratliff:
Implicit Learning Dynamics in Stackelberg Games: Equilibria Characterization, Convergence Analysis, and Empirical Study. ICML 2020: 3133-3144 - [c6]Tanner Fiez, Nihar B. Shah, Lillian J. Ratliff:
A SUPER* Algorithm to Optimize Paper Bidding in Peer Review. UAI 2020: 580-589 - [i9]Tanner Fiez, Nihar B. Shah, Lillian J. Ratliff:
A SUPER* Algorithm to Optimize Paper Bidding in Peer Review. CoRR abs/2007.07079 (2020) - [i8]Tanner Fiez, Lillian J. Ratliff:
Gradient Descent-Ascent Provably Converges to Strict Local Minmax Equilibria with a Finite Timescale Separation. CoRR abs/2009.14820 (2020) - [i7]Stratis Skoulakis, Tanner Fiez, Ryann Sim, Georgios Piliouras, Lillian J. Ratliff:
Evolutionary Game Theory Squared: Evolving Agents in Endogenously Evolving Zero-Sum Games. CoRR abs/2012.08382 (2020)
2010 – 2019
- 2019
- [j1]Lillian J. Ratliff, Roy Dong, Shreyas Sekar, Tanner Fiez:
A Perspective on Incentive Design: Challenges and Opportunities. Annu. Rev. Control. Robotics Auton. Syst. 2: 305-338 (2019) - [c5]Tanner Fiez, Lalit Jain, Kevin G. Jamieson, Lillian J. Ratliff:
Sequential Experimental Design for Transductive Linear Bandits. NeurIPS 2019: 10666-10676 - [i6]Tanner Fiez, Benjamin Chasnov, Lillian J. Ratliff:
Convergence of Learning Dynamics in Stackelberg Games. CoRR abs/1906.01217 (2019) - [i5]Tanner Fiez, Lalit Jain, Kevin G. Jamieson, Lillian J. Ratliff:
Sequential Experimental Design for Transductive Linear Bandits. CoRR abs/1906.08399 (2019) - 2018
- [c4]Tanner Fiez, Lillian J. Ratliff
Data Driven Spatio-Temporal Modeling of Parking Demand. ACC 2018: 2757-2762 - [c3]Tanner Fiez, Shreyas Sekar, Liyuan Zheng, Lillian J. Ratliff:
Combinatorial Bandits for Incentivizing Agents with Dynamic Preferences. UAI 2018: 693-703 - [i4]Lillian J. Ratliff, Shreyas Sekar, Liyuan Zheng, Tanner Fiez:
Incentives in the Dark: Multi-armed Bandits for Evolving Users with Unknown Type. CoRR abs/1803.04008 (2018) - [i3]Lillian J. Ratliff, Tanner Fiez:
Adaptive Incentive Design. CoRR abs/1806.05749 (2018) - [i2]Tanner Fiez, Shreyas Sekar, Liyuan Zheng, Lillian J. Ratliff:
Combinatorial Bandits for Incentivizing Agents with Dynamic Preferences. CoRR abs/1807.02297 (2018) - 2017
- [c2]Chase Dowling, Tanner Fiez, Lillian J. Ratliff
Optimizing curbside parking resources subject to congestion constraints. CDC 2017: 5080-5085 - [c1]Eric Mazumdar, Lillian J. Ratliff
Gradient-based inverse risk-sensitive reinforcement learning. CDC 2017: 5796-5801 - [i1]Chase Dowling, Tanner Fiez, Lillian J. Ratliff, Baosen Zhang:
How Much Urban Traffic is Searching for Parking? CoRR abs/1702.06156 (2017)
Coauthor Index
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