| 2026 | COLT | Online Learning for Uninformed Markov Games: Empirical Nash-Value Regret and Non-Stationarity Adaptation. | Junyan Liu, Haipeng Luo, Zihan Zhang, Lillian J. Ratliff |
| 2025 | COLT | 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 |
| 2025 | ICML | S4S: Solving for a Fast Diffusion Model Solver. | Eric Frankel, Sitan Chen, Jerry Li, Pang Wei Koh, Lillian J. Ratliff, Sewoong Oh |
| 2025 | ICML | Finite-Time Convergence Rates in Stochastic Stackelberg Games with Smooth Algorithmic Agents. | Eric Frankel, Kshitij Kulkarni, Dmitriy Drusvyatskiy, Sewoong Oh, Lillian J. Ratliff |
| 2025 | ICML | Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals. | Junyan Liu, Arnab Maiti, Artin Tajdini, Kevin Jamieson, Lillian J. Ratliff |
| 2025 | ICML | Principal-Agent Bandit Games with Self-Interested and Exploratory Learning Agents. | Junyan Liu, Lillian J. Ratliff |
| 2025 | IROS | Safe Probabilistic Planning for Human-Robot Interaction using Conformal Risk Control. | Jake Gonzales, Kazuki Mizuta, Karen Leung, Lillian J. Ratliff |
| 2025 | SAGT | On the Limitations and Possibilities of Nash Regret Minimization in Zero-Sum Matrix Games Under Noisy Feedback. | Arnab Maiti, Kevin Jamieson, Lillian J. Ratliff |
| 2024 | AISTATS | Emergent specialization from participation dynamics and multi-learner retraining. | Sarah Dean, Mihaela Curmei, Lillian J. Ratliff, Jamie Morgenstern, Maryam Fazel |
| 2024 | AISTATS | Near-Optimal Pure Exploration in Matrix Games: A Generalization of Stochastic Bandits & Dueling Bandits. | Arnab Maiti, Ross Boczar, Kevin Jamieson, Lillian J. Ratliff |
| 2024 | UAI | Efficient Interactive Maximization of BP and Weakly Submodular Objectives. | Adhyyan Narang, Omid Sadeghi, Lillian J. Ratliff, Maryam Fazel, Jeff A. Bilmes |
| 2023 | AISTATS | Approximate Regions of Attraction in Learning with Decision-Dependent Distributions. | Roy Dong, Heling Zhang, Lillian J. Ratliff |
| 2023 | AISTATS | Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games. | Arnab Maiti, Kevin Jamieson, Lillian J. Ratliff |
| 2023 | ICRA | Stackelberg Games for Learning Emergent Behaviors During Competitive Autocurricula. | Boling Yang, Liyuan Zheng, Lillian J. Ratliff, Byron Boots, Joshua R. Smith |
| 2022 | AAAI | Decision-Dependent Risk Minimization in Geometrically Decaying Dynamic Environments. | Mitas Ray, Lillian J. Ratliff, Dmitriy Drusvyatskiy, Maryam Fazel |
| 2022 | AAAI | Stackelberg Actor-Critic: Game-Theoretic Reinforcement Learning Algorithms. | Liyuan Zheng, Tanner Fiez, Zane Alumbaugh, Benjamin Chasnov, Lillian J. Ratliff |
| 2022 | AISTATS | Zeroth-Order Methods for Convex-Concave Min-max Problems: Applications to Decision-Dependent Risk Minimization. | Chinmay Maheshwari, Chih-Yuan Chiu, Eric Mazumdar, Shankar Sastry, Lillian J. Ratliff |
| 2022 | AISTATS | Learning in Stochastic Monotone Games with Decision-Dependent Data. | Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff |
| 2022 | ICLR | Minimax Optimization with Smooth Algorithmic Adversaries. | Tanner Fiez, Chi Jin, Praneeth Netrapalli, Lillian J. Ratliff |
| 2022 | SAGT | Fast Convergence of Optimistic Gradient Ascent in Network Zero-Sum Extensive Form Games. | Georgios Piliouras, Lillian J. Ratliff, Ryann Sim, Stratis Skoulakis |
| 2021 | AAAI | Evolutionary Game Theory Squared: Evolving Agents in Endogenously Evolving Zero-Sum Games. | Stratis Skoulakis, Tanner Fiez, Ryann Sim, Georgios Piliouras, Lillian J. Ratliff |
| 2021 | ICLR | Local Convergence Analysis of Gradient Descent Ascent with Finite Timescale Separation. | Tanner Fiez, Lillian J. Ratliff |
| 2020 | ICML | Implicit Learning Dynamics in Stackelberg Games: Equilibria Characterization, Convergence Analysis, and Empirical Study. | Tanner Fiez, Benjamin Chasnov, Lillian J. Ratliff |
| 2020 | UAI | A SUPER* Algorithm to Optimize Paper Bidding in Peer Review. | Tanner Fiez, Nihar B. Shah, Lillian J. Ratliff |
| 2019 | UAI | Convergence Analysis of Gradient-Based Learning in Continuous Games. | Benjamin Chasnov, Lillian J. Ratliff, Eric Mazumdar, Samuel Burden |
| 2019 | SmartComp | Mobilytics-Gym: A Simulation Framework for Analyzing Urban Mobility Decision Strategies. | Chinmaya Samal, Abhishek Dubey, Lillian J. Ratliff |
| 2018 | UAI | Combinatorial Bandits for Incentivizing Agents with Dynamic Preferences. | Tanner Fiez, Shreyas Sekar, Liyuan Zheng, Lillian J. Ratliff |
| 2018 | SmartComp | Mobilytics- An Extensible, Modular and Resilient Mobility Platform. | Chinmaya Samal, Abhishek Dubey, Lillian J. Ratliff |