Lillian J. Ratliff

ORCID

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 121

Top Venues

Publications

Heling Zhang, Lillian J. Ratliff, Roy Dong
Distribution-Free Guarantees for Systems with Decision-Dependent Noise. CoRR (2024)
Arnab Maiti, Ross Boczar, Kevin G. Jamieson, Lillian J. Ratliff
Near-Optimal Pure Exploration in Matrix Games: A Generalization of Stochastic Bandits & Dueling Bandits. AISTATS (2024)
Sarah Dean, Mihaela Curmei, Lillian J. Ratliff, Jamie Morgenstern, Maryam Fazel
Emergent specialization from participation dynamics and multi-learner retraining. AISTATS (2024)
Adhyyan Narang, Andrew Wagenmaker, Lillian J. Ratliff, Kevin G. Jamieson
Sample Complexity Reduction via Policy Difference Estimation in Tabular Reinforcement Learning. CoRR (2024)
Daniel J. Calderone, Benjamin J. Chasnov, Samuel A. Burden, Lillian J. Ratliff
Consistent Conjectural Variations Equilibrium: Characterization & Stability for a Class of Continuous Games. CoRR (2023)
Daniel J. Calderone, Benjamin J. Chasnov, Samuel A. Burden, Lillian J. Ratliff
Consistent Conjectural Variations Equilibria: Characterization and Stability for a Class of Continuous Games. IEEE Control. Syst. Lett. 7 (2023)
Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff
Multiplayer Performative Prediction: Learning in Decision-Dependent Games. J. Mach. Learn. Res. 24 (2023)
Lauren E. Conger, Franca Hoffmann, Eric Mazumdar, Lillian J. Ratliff
Coupled Gradient Flows for Strategic Non-Local Distribution Shift. CoRR (2023)
Arnab Maiti, Kevin G. Jamieson, Lillian J. Ratliff
Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games. AISTATS (2023)
Boling Yang, Liyuan Zheng, Lillian J. Ratliff, Byron Boots, Joshua R. Smith
Stackelberg Games for Learning Emergent Behaviors During Competitive Autocurricula. CoRR (2023)
Arnab Maiti, Ross Boczar, Kevin G. Jamieson, Lillian J. Ratliff
Query-Efficient Algorithms to Find the Unique Nash Equilibrium in a Two-Player Zero-Sum Matrix Game. CoRR (2023)
Roy Dong, Heling Zhang, Lillian J. Ratliff
Approximate Regions of Attraction in Learning with Decision-Dependent Distributions. AISTATS (2023)
Arnab Maiti, Kevin G. Jamieson, Lillian J. Ratliff
Logarithmic Regret for Matrix Games against an Adversary with Noisy Bandit Feedback. CoRR (2023)
Arnab Maiti, Ross Boczar, Kevin G. Jamieson, Lillian J. Ratliff
Near-Optimal Pure Exploration in Matrix Games: A Generalization of Stochastic Bandits & Dueling Bandits. CoRR (2023)
Benjamin J. Chasnov, Lillian J. Ratliff, Samuel A. Burden
Human adaptation to adaptive machines converges to game-theoretic equilibria. CoRR (2023)
Chinmay Maheshwari, S. Shankar Sastry, Lillian J. Ratliff, Eric Mazumdar
Convergent First-Order Methods for Bi-level Optimization and Stackelberg Games. CoRR (2023)
Sarah H. Q. Li, Yue Yu, Nicolas I. Miguel, Daniel J. Calderone, Lillian J. Ratliff, Behçet Açikmese
Adaptive constraint satisfaction for Markov decision process congestion games: Application to transportation networks. Autom. 151 (2023)
Lauren E. Conger, Franca Hoffmann, Eric Mazumdar, Lillian J. Ratliff
Strategic Distribution Shift of Interacting Agents via Coupled Gradient Flows. NeurIPS (2023)
Boling Yang, Liyuan Zheng, Lillian J. Ratliff, Byron Boots, Joshua R. Smith
Stackelberg Games for Learning Emergent Behaviors During Competitive Autocurricula. ICRA (2023)
Avinandan Bose, Mihaela Curmei, Daniel L. Jiang, Jamie Morgenstern, Sarah Dean, Lillian J. Ratliff, Maryam Fazel
Initializing Services in Interactive ML Systems for Diverse Users. CoRR (2023)
Arnab Maiti, Kevin G. Jamieson, Lillian J. Ratliff
Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games. CoRR (2023)
Esther Ling, Liyuan Zheng, Lillian J. Ratliff, Samuel Coogan
Koopman Operator Applications in Signalized Traffic Systems. IEEE Trans. Intell. Transp. Syst. 23 (4) (2022)
Georgios Piliouras, Lillian J. Ratliff, Ryann Sim, Stratis Skoulakis
Fast Convergence of Optimistic Gradient Ascent in Network Zero-Sum Extensive Form Games. SAGT (2022)
Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff
Learning in Stochastic Monotone Games with Decision-Dependent Data. AISTATS (2022)
Sarah H. Q. Li, Lillian J. Ratliff, Peeyush Kumar
General sum stochastic games with networked information flows. CoRR (2022)
Chinmay Maheshwari, Chih-Yuan Chiu, Eric Mazumdar, Shankar Sastry, Lillian J. Ratliff
Zeroth-Order Methods for Convex-Concave Min-max Problems: Applications to Decision-Dependent Risk Minimization. AISTATS (2022)
Liyuan Zheng, Tanner Fiez, Zane Alumbaugh, Benjamin Chasnov, Lillian J. Ratliff
Stackelberg Actor-Critic: Game-Theoretic Reinforcement Learning Algorithms. AAAI (2022)
Yue Yu, Daniel J. Calderone, Sarah H. Q. Li, Lillian J. Ratliff, Behçet Açikmese
Variable demand and multi-commodity flow in Markovian network equilibrium. Autom. 140 (2022)
Sarah Dean, Mihaela Curmei, Lillian J. Ratliff, Jamie Morgenstern, Maryam Fazel
Multi-learner risk reduction under endogenous participation dynamics. CoRR (2022)
Zhaoqi Li, Lillian J. Ratliff, Houssam Nassif, Kevin G. Jamieson, Lalit Jain
Instance-optimal PAC Algorithms for Contextual Bandits. CoRR (2022)
Zhaoqi Li, Lillian J. Ratliff, Houssam Nassif, Kevin G. Jamieson, Lalit Jain
Instance-optimal PAC Algorithms for Contextual Bandits. NeurIPS (2022)
Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff
Multiplayer Performative Prediction: Learning in Decision-Dependent Games. CoRR (2022)
Tanner Fiez, Chi Jin, Praneeth Netrapalli, Lillian J. Ratliff
Minimax Optimization with Smooth Algorithmic Adversaries. ICLR (2022)
Mitas Ray, Lillian J. Ratliff, Dmitriy Drusvyatskiy, Maryam Fazel
Decision-Dependent Risk Minimization in Geometrically Decaying Dynamic Environments. AAAI (2022)
Georgios Piliouras, Lillian J. Ratliff, Ryann Sim, Stratis Skoulakis
Fast Convergence of Optimistic Gradient Ascent in Network Zero-Sum Extensive Form Games. CoRR (2022)
Mitas Ray, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff
Decision-Dependent Risk Minimization in Geometrically Decaying Dynamic Environments. CoRR (2022)
Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff
. CDC (2022)
Adhyyan Narang, Omid Sadeghi, Lillian J. Ratliff, Maryam Fazel, Jeff A. Bilmes
Interactive Combinatorial Bandits: Balancing Competitivity and Complementarity. CoRR (2022)
Stratis Skoulakis, Tanner Fiez, Ryann Sim, Georgios Piliouras, Lillian J. Ratliff
Evolutionary Game Theory Squared: Evolving Agents in Endogenously Evolving Zero-Sum Games. AAAI (2021)
Dmitriy Drusvyatskiy, Lillian J. Ratliff
Improved rates for derivative free play in convex games. CoRR (2021)
Tanner Fiez, Ryann Sim, Stratis Skoulakis, Georgios Piliouras, Lillian J. Ratliff
Online Learning in Periodic Zero-Sum Games. CoRR (2021)
Tanner Fiez, Lillian J. Ratliff
Local Convergence Analysis of Gradient Descent Ascent with Finite Timescale Separation. ICLR (2021)
Sarah H. Q. Li, Lillian J. Ratliff, Behçet Açikmese
Disturbance Decoupling for Gradient-Based Multi-Agent Learning With Quadratic Costs. IEEE Control. Syst. Lett. 5 (1) (2021)
Liyuan Zheng, Yuanyuan Shi, Lillian J. Ratliff, Baosen Zhang
Safe Reinforcement Learning of Control-Affine Systems with Vertex Networks. L4DC (2021)
Roy Dong, Lillian J. Ratliff
Which Echo Chamber? Regions of Attraction in Learning with Decision-Dependent Distributions. CoRR (2021)
Tanner Fiez, Chi Jin, Praneeth Netrapalli, Lillian J. Ratliff
Minimax Optimization with Smooth Algorithmic Adversaries. CoRR (2021)
Tanner Fiez, Ryann Sim, Stratis Skoulakis, Georgios Piliouras, Lillian J. Ratliff
Online Learning in Periodic Zero-Sum Games. NeurIPS (2021)
Chinmay Maheshwari, Chih-Yuan Chiu, Eric Mazumdar, S. Shankar Sastry, Lillian J. Ratliff
Zeroth-Order Methods for Convex-Concave Minmax Problems: Applications to Decision-Dependent Risk Minimization. CoRR (2021)
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)
Liyuan Zheng, Tanner Fiez, Zane Alumbaugh, Benjamin Chasnov, Lillian J. Ratliff
Stackelberg Actor-Critic: Game-Theoretic Reinforcement Learning Algorithms. CoRR (2021)
Lillian J. Ratliff, Tanner Fiez
Adaptive Incentive Design. IEEE Trans. Autom. Control. 66 (8) (2021)
Stratis Skoulakis, Tanner Fiez, Ryann Sim, Georgios Piliouras, Lillian J. Ratliff
Evolutionary Game Theory Squared: Evolving Agents in Endogenously Evolving Zero-Sum Games. CoRR (2020)
Benjamin J. Chasnov, Daniel J. Calderone, Behçet Açikmese, Samuel A. Burden, Lillian J. Ratliff
Stability of Gradient Learning Dynamics in Continuous Games: Vector Action Spaces. CoRR (2020)
Benjamin J. Chasnov, Daniel J. Calderone, Behçet Açikmese, Samuel A. Burden, Lillian J. Ratliff
Stability of Gradient Learning Dynamics in Continuous Games: Scalar Action Spaces. CDC (2020)
Shreyas Sekar, Liyuan Zheng, Lillian J. Ratliff, Baosen Zhang
Uncertainty in Multicommodity Routing Networks: When Does It Help? IEEE Trans. Autom. Control. 65 (11) (2020)
Tanner Fiez, Benjamin Chasnov, Lillian J. Ratliff
Implicit Learning Dynamics in Stackelberg Games: Equilibria Characterization, Convergence Analysis, and Empirical Study. ICML (2020)
Eric Mazumdar, Lillian J. Ratliff, S. Shankar Sastry
On Gradient-Based Learning in Continuous Games. SIAM J. Math. Data Sci. 2 (1) (2020)
Tanner Fiez, Lillian J. Ratliff
Gradient Descent-Ascent Provably Converges to Strict Local Minmax Equilibria with a Finite Timescale Separation. CoRR (2020)
Tanner Fiez, Lillian J. Ratliff
Gaussian Mixture Models for Parking Demand Data. IEEE Trans. Intell. Transp. Syst. 21 (8) (2020)
Tanner Fiez, Nihar B. Shah, Lillian J. Ratliff
Algorithm to Optimize Paper Bidding in Peer Review. CoRR (2020)
Mitas Ray, Omid Sadeghi, Lillian J. Ratliff, Maryam Fazel
Function Design for Improved Competitive Ratio in Online Resource Allocation with Procurement Costs. CoRR (2020)
Eric Mazumdar, Lillian J. Ratliff
Local Nash Equilibria are Isolated, Strict Local Nash Equilibria in 'Almost All' Zero-Sum Continuous Games. CoRR (2020)
Liyuan Zheng, Lillian J. Ratliff
Constrained Upper Confidence Reinforcement Learning. CoRR (2020)
Liyuan Zheng, Lillian J. Ratliff
Constrained Upper Confidence Reinforcement Learning. L4DC (2020)
Liyuan Zheng, Yuanyuan Shi, Lillian J. Ratliff, Baosen Zhang
Safe Reinforcement Learning of Control-Affine Systems with Vertex Networks. CoRR (2020)
Chase P. Dowling, Lillian J. Ratliff, Baosen Zhang
Modeling Curbside Parking as a Network of Finite Capacity Queues. IEEE Trans. Intell. Transp. Syst. 21 (3) (2020)
Sarah H. Q. Li, Lillian J. Ratliff, Behçet Açikmese
Disturbance Decoupling for Gradient-based Multi-Agent Learning with Quadratic Costs. CoRR (2020)
Tanner Fiez, Nihar B. Shah, Lillian J. Ratliff
A SUPER* Algorithm to Optimize Paper Bidding in Peer Review. UAI (2020)
Benjamin J. Chasnov, Daniel J. Calderone, Behçet Açikmese, Samuel A. Burden, Lillian J. Ratliff
Stability of Gradient Learning Dynamics in Continuous Games: Scalar Action Spaces. CoRR (2020)
Lillian J. Ratliff, Eric Mazumdar
Inverse Risk-Sensitive Reinforcement Learning. IEEE Trans. Autom. Control. 65 (3) (2020)
Tyler Westenbroek, Roy Dong, Lillian J. Ratliff, S. Shankar Sastry
Competitive Statistical Estimation With Strategic Data Sources. IEEE Trans. Autom. Control. 65 (4) (2020)
Eric Mazumdar, Lillian J. Ratliff, Michael I. Jordan, S. Shankar Sastry
Policy-Gradient Algorithms Have No Guarantees of Convergence in Linear Quadratic Games. AAMAS (2020)
Benjamin Chasnov, Lillian J. Ratliff, Eric Mazumdar, Samuel Burden
Convergence Analysis of Gradient-Based Learning in Continuous Games. UAI (2019)
Eric Mazumdar, Lillian J. Ratliff
Local Nash Equilibria are Isolated, Strict Local Nash Equilibria in 'Almost All' Zero-Sum Continuous Games. CDC (2019)
Tanner Fiez, Benjamin Chasnov, Lillian J. Ratliff
Convergence of Learning Dynamics in Stackelberg Games. CoRR (2019)
Shahriar Talebi, Siavash Alemzadeh, Lillian J. Ratliff, Mehran Mesbahi
Distributed Learning in Network Games: a Dual Averaging Approach. CDC (2019)
Daniel J. Calderone, Lillian J. Ratliff
Multi-Dimensional Continuous Type Population Potential Games. CDC (2019)
Lillian J. Ratliff, Roy Dong, Shreyas Sekar, Tanner Fiez
A Perspective on Incentive Design: Challenges and Opportunities. Annu. Rev. Control. Robotics Auton. Syst. 2 (2019)
Chinmaya Samal, Abhishek Dubey, Lillian J. Ratliff
Mobilytics-Gym: A Simulation Framework for Analyzing Urban Mobility Decision Strategies. SMARTCOMP (2019)
Tanner Fiez, Lalit Jain, Kevin G. Jamieson, Lillian J. Ratliff
Sequential Experimental Design for Transductive Linear Bandits. CoRR (2019)
Sarah H. Q. Li, Yue Yu, Daniel J. Calderone, Lillian J. Ratliff, Behçet Açikmese
Tolling for Constraint Satisfaction in Markov Decision Process Congestion Games. ACC (2019)
Jingjing Bu, Lillian J. Ratliff, Mehran Mesbahi
Global Convergence of Policy Gradient for Sequential Zero-Sum Linear Quadratic Dynamic Games. CoRR (2019)
Tyler Westenbroek, Roy Dong, Lillian J. Ratliff, S. Shankar Sastry
Competitive Statistical Estimation with Strategic Data Sources. CoRR (2019)
Sarah H. Q. Li, Yue Yu, Daniel J. Calderone, Lillian J. Ratliff, Behçet Açikmese
Tolling for Constraint Satisfaction in Markov Decision Process Congestion Games. CoRR (2019)
Sarah H. Q. Li, Yue Yu, Daniel J. Calderone, Lillian J. Ratliff, Behçet Açikmese
Online Constraint Satisfaction via Tolls in MDP Congestion Games. CoRR (2019)
Eric Mazumdar, Lillian J. Ratliff, Michael I. Jordan, S. Shankar Sastry
Policy-Gradient Algorithms Have No Guarantees of Convergence in Continuous Action and State Multi-Agent Settings. CoRR (2019)
Sarah H. Q. Li, Daniel J. Calderone, Lillian J. Ratliff, Behçet Açikmese
Sensitivity Analysis for Markov Decision Process Congestion Games. CDC (2019)
Tanner Fiez, Lalit Jain, Kevin G. Jamieson, Lillian J. Ratliff
Sequential Experimental Design for Transductive Linear Bandits. NeurIPS (2019)
Benjamin Chasnov, Lillian J. Ratliff, Eric Mazumdar, Samuel A. Burden
Convergence Analysis of Gradient-Based Learning with Non-Uniform Learning Rates in Non-Cooperative Multi-Agent Settings. CoRR (2019)
Yagiz Savas, Vijay Gupta, Melkior Ornik, Lillian J. Ratliff, Ufuk Topcu
Incentive Design for Temporal Logic Objectives. CDC (2019)
Sarah H. Q. Li, Daniel J. Calderone, Lillian J. Ratliff, Behçet Açikmese
Sensitivity Analysis for Markov Decision Process Congestion Games. CoRR (2019)
Eric Mazumdar, Lillian J. Ratliff
On the Convergence of Competitive, Multi-Agent Gradient-Based Learning. CoRR (2018)
Tanner Fiez, Shreyas Sekar, Liyuan Zheng, Lillian J. Ratliff
Combinatorial Bandits for Incentivizing Agents with Dynamic Preferences. UAI (2018)
Ioannis C. Konstantakopoulos, Lillian J. Ratliff, Ming Jin, S. Shankar Sastry, Costas J. Spanos
A Robust Utility Learning Framework via Inverse Optimization. IEEE Trans. Control. Syst. Technol. 26 (3) (2018)
Chinmaya Samal, Liyuan Zheng, Fangzhou Sun, Lillian J. Ratliff, Abhishek Dubey
Towards a Socially Optimal Multi-Modal Routing Platform. CoRR (2018)
Chinmaya Samal, Abhishek Dubey, Lillian J. Ratliff
Mobilytics- An Extensible, Modular and Resilient Mobility Platform. SMARTCOMP (2018)
Lillian J. Ratliff, Shreyas Sekar, Liyuan Zheng, Tanner Fiez
Incentives in the Dark: Multi-armed Bandits for Evolving Users with Unknown Type. CoRR (2018)
Tanner Fiez, Shreyas Sekar, Liyuan Zheng, Lillian J. Ratliff
Combinatorial Bandits for Incentivizing Agents with Dynamic Preferences. CoRR (2018)
Lillian J. Ratliff, Tanner Fiez
Adaptive Incentive Design. CoRR (2018)
Roy Dong, Lillian J. Ratliff, Alvaro A. Cárdenas, Henrik Ohlsson, S. Shankar Sastry
Quantifying the Utility-Privacy Tradeoff in the Internet of Things. ACM Trans. Cyber Phys. Syst. 2 (2) (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

Lillian J. Ratliff