Ratliff, Lillian J.

20 publications

COLT 2025 Efficient Near-Optimal Algorithm for Online Shortest Paths in Directed Acyclic Graphs with Bandit Feedback Against Adaptive Adversaries Arnab Maiti, Zhiyuan Fan, Kevin Jamieson, Lillian J. Ratliff, Gabriele Farina

ICML 2025 Finite-Time Convergence Rates in Stochastic Stackelberg Games with Smooth Algorithmic Agents Eric Frankel, Kshitij Kulkarni, Dmitriy Drusvyatskiy, Sewoong Oh, Lillian J. Ratliff

NeurIPS 2025 Improved Regret and Contextual Linear Extension for Pandora's Box and Prophet Inequality Junyan Liu, Ziyun Chen, Kun Wang, Haipeng Luo, Lillian J. Ratliff

ICML 2025 Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals Junyan Liu, Arnab Maiti, Artin Tajdini, Kevin Jamieson, Lillian J. Ratliff

NeurIPS 2025 On the Universal near Optimality of Hedge in Combinatorial Settings Zhiyuan Fan, Arnab Maiti, Lillian J. Ratliff, Kevin Jamieson, Gabriele Farina

ICML 2025 Principal-Agent Bandit Games with Self-Interested and Exploratory Learning Agents Junyan Liu, Lillian J. Ratliff

ICML 2025 S4S: Solving for a Fast Diffusion Model Solver Eric Frankel, Sitan Chen, Jerry Li, Pang Wei Koh, Lillian J. Ratliff, Sewoong Oh

NeurIPS 2024 Initializing Services in Interactive ML Systems for Diverse Users Avinandan Bose, Mihaela Curmei, Daniel L. Jiang, Jamie Morgenstern, Sarah Dean, Lillian J. Ratliff, Maryam Fazel

NeurIPS 2024 Sample Complexity Reduction via Policy Difference Estimation in Tabular Reinforcement Learning Adhyyan Narang, Andrew Wagenmaker, Lillian J. Ratliff, Kevin Jamieson

ICMLW 2023 Coupled Gradient Flows for Strategic Non-Local Distribution Shift Lauren Conger, Franca Hoffmann, Eric Mazumdar, Lillian J. Ratliff

JMLR 2023 Multiplayer Performative Prediction: Learning in Decision-Dependent Games Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff

AAAI 2022 Decision-Dependent Risk Minimization in Geometrically Decaying Dynamic Environments Mitas Ray, Lillian J. Ratliff, Dmitriy Drusvyatskiy, Maryam Fazel

ICLRW 2022 General Sum Stochastic Games with Networked Information Flow Sarah Li, Lillian J Ratliff, Peeyush Kumar

ICLR 2022 Minimax Optimization with Smooth Algorithmic Adversaries Tanner Fiez, Chi Jin, Praneeth Netrapalli, Lillian J Ratliff

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

ICLRW 2022 Stackelberg Policy Gradient: Evaluating the Performance of Leaders and Followers Quoc-Liem Vu, Zane Alumbaugh, Ryan Ching, Quanchen Ding, Arnav Mahajan, Benjamin Chasnov, Sam Burden, Lillian J Ratliff

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

ICLR 2021 Local Convergence Analysis of Gradient Descent Ascent with Finite Timescale Separation Tanner Fiez, Lillian J Ratliff

L4DC 2021 Safe Reinforcement Learning of Control-Affine Systems with Vertex Networks Liyuan Zheng, Yuanyuan Shi, Lillian J. Ratliff, Baosen Zhang

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