Lillian J. Ratliff

171 papers A* 19A 12B 4C 7Journal 98Unranked 31

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Dynamics of Learning under User Choice: Overspecialization and Peer-Model Probing. CoRR Adhyyan Narang, Sarah Dean, Lillian J. Ratliff, Maryam Fazel
2026	J	`jnl`	Efficient Uncoupled Learning Dynamics with ~O}(T CoRR Arnab Maiti, Claire Jie Zhang, Kevin Jamieson, Jamie H. Morgenstern, Ioannis Panageas, Lillian J. Ratliff
2026	J	`jnl`	Online Learning for Uninformed Markov Games: Empirical Nash-Value Regret and Non-Stationarity Adaptation. CoRR Junyan Liu, Haipeng Luo, Zihan Zhang, Lillian J. Ratliff
2026	J	`jnl`	Revisiting the Bertrand Paradox via Equilibrium Analysis of No-regret Learners. CoRR Arnab Maiti, Junyan Liu, Kevin Jamieson, Lillian J. Ratliff
2026	J	`jnl`	Safe Probabilistic Planning for Human-Robot Interaction using Conformal Risk Control. CoRR Jake Gonzales, Kazuki Mizuta, Karen Leung, Lillian J. Ratliff
2026	J	`jnl`	Strategically Robust Multi-Agent Reinforcement Learning with Linear Function Approximation. CoRR Jake Gonzales, Max Horwitz, Eric Mazumdar, Lillian J. Ratliff
2026	J	`jnl`	TOPReward: Token Probabilities as Hidden Zero-Shot Rewards for Robotics. CoRR Shirui Chen, Cole Harrison, Ying-Chun Lee, Angela Jin Yang, Zhongzheng Ren, Lillian J. Ratliff, Jiafei Duan, Dieter Fox, Ranjay Krishna
2025	J	`jnl`	A Learning Algorithm That Attains the Human Optimum in a Repeated Human-Machine Interaction Game. CoRR Jason T. Isa, Lillian J. Ratliff, Samuel A. Burden
2025	A*	`conf`	Efficient Near-Optimal Algorithm for Online Shortest Paths in Directed Acyclic Graphs with Bandit Feedback Against Adaptive Adversaries. COLT Arnab Maiti, Zhiyuan Fan, Kevin Jamieson, Lillian J. Ratliff, Gabriele Farina
2025	J	`jnl`	Efficient Near-Optimal Algorithm for Online Shortest Paths in Directed Acyclic Graphs with Bandit Feedback Against Adaptive Adversaries. CoRR Arnab Maiti, Zhiyuan Fan, Kevin Jamieson, Lillian J. Ratliff, Gabriele Farina
2025	A*	`conf`	Finite-Time Convergence Rates in Stochastic Stackelberg Games with Smooth Algorithmic Agents. ICML Eric Frankel, Kshitij Kulkarni, Dmitriy Drusvyatskiy, Sewoong Oh, Lillian J. Ratliff
2025	J	`jnl`	Function Design for Improved Competitive Ratio in Online Resource Allocation with Procurement Costs. INFORMS J. Optim. Mitas Ray, Omid Sadeghi, Lillian J. Ratliff, Maryam Fazel
2025	J	`jnl`	Improved Regret and Contextual Linear Extension for Pandora's Box and Prophet Inequality. CoRR Junyan Liu, Ziyun Chen, Kun Wang, Haipeng Luo, Lillian J. Ratliff
2025	A*	`conf`	Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals. ICML Junyan Liu, Arnab Maiti, Artin Tajdini, Kevin Jamieson, Lillian J. Ratliff
2025	J	`jnl`	Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals. CoRR Junyan Liu, Arnab Maiti, Artin Tajdini, Kevin Jamieson, Lillian J. Ratliff
2025	B	`conf`	On the Limitations and Possibilities of Nash Regret Minimization in Zero-Sum Matrix Games Under Noisy Feedback. SAGT Arnab Maiti, Kevin Jamieson, Lillian J. Ratliff
2025	J	`jnl`	On the Universal Near Optimality of Hedge in Combinatorial Settings. CoRR Zhiyuan Fan, Arnab Maiti, Kevin Jamieson, Lillian J. Ratliff, Gabriele Farina
2025	A*	`conf`	Principal-Agent Bandit Games with Self-Interested and Exploratory Learning Agents. ICML Junyan Liu, Lillian J. Ratliff
2025	J	`jnl`	Query-Efficient Algorithm to Find all Nash Equilibria in a Two-Player Zero-Sum Matrix Game. ACM Trans. Economics and Comput. Arnab Maiti, Ross Boczar, Kevin Jamieson, Lillian J. Ratliff
2025	J	`jnl`	S4S: Solving for a Diffusion Model Solver. CoRR Eric Frankel, Sitan Chen, Jerry Li, Pang Wei Koh, Lillian J. Ratliff, Sewoong Oh
2025	A*	`conf`	S4S: Solving for a Fast Diffusion Model Solver. ICML Eric Frankel, Sitan Chen, Jerry Li, Pang Wei Koh, Lillian J. Ratliff, Sewoong Oh
2025	A	`conf`	Safe Probabilistic Planning for Human-Robot Interaction using Conformal Risk Control. IROS Jake Gonzales, Kazuki Mizuta, Karen Leung, Lillian J. Ratliff
2025	J	`jnl`	Stow: Robotic Packing of Items into Fabric Pods. CoRR Nicolas Hudson, Josh Hooks, Rahul Warrier, Curt Salisbury, Ross Hartley, Kislay Kumar, Bhavana Chandrashekhar, Paul Birkmeyer, Bosch Tang, Matthew A. Frost, Shantanu Thakar, Tony Piaskowy, Petter Nilsson, Josh Petersen, Neel Doshi, Alan Slatter, Ankit Bhatia, Cassie Meeker, Yuechuan Xue, Dylan Cox, Alex Kyriazis, Bai Lou, Nadeem Hasan, Asif Rana, Nikhil Chacko, Ruinian Xu, Siamak Faal, Esi Seraj, Mudit Agrawal, Kevin Jamieson, Alessio Bisagni, Valerie Samzun, Christine Fuller, Alex Keklak, Alex Frenkel, Lillian J. Ratliff, Aaron Parness
2025	J	`jnl`	dUltra: Ultra-Fast Diffusion Language Models via Reinforcement Learning. CoRR Shirui Chen, Jiantao Jiao, Lillian J. Ratliff, Banghua Zhu
2024	J	`jnl`	Distribution-Free Guarantees for Systems with Decision-Dependent Noise. CoRR Heling Zhang, Lillian J. Ratliff, Roy Dong
2024	J	`jnl`	Effect of Adaptation Rate and Cost Display in a Human-AI Interaction Game. CoRR Jason T. Isa, Bohan Wu, Qirui Wang, Yilin Zhang, Samuel A. Burden, Lillian J. Ratliff, Benjamin J. Chasnov
2024	A	`conf`	Efficient Interactive Maximization of BP and Weakly Submodular Objectives. UAI Adhyyan Narang, Omid Sadeghi, Lillian J. Ratliff, Maryam Fazel, Jeff A. Bilmes
2024	A	`conf`	Emergent specialization from participation dynamics and multi-learner retraining. AISTATS Sarah Dean, Mihaela Curmei, Lillian J. Ratliff, Jamie Morgenstern, Maryam Fazel
2024	—	`conf`	Follower Agnostic Learning in Stackelberg Games. CDC Chinmay Maheshwari, James Cheng, Shankar Sastry, Lillian J. Ratliff, Eric Mazumdar
2024	A*	`conf`	Initializing Services in Interactive ML Systems for Diverse Users. NeurIPS Avinandan Bose, Mihaela Curmei, Daniel L. Jiang, Jamie H. Morgenstern, Sarah Dean, Lillian J. Ratliff, Maryam Fazel
2024	C	`conf`	Learning in Stochastic Stackelberg Games. ACC Pranoy Das, Benita Nortmann, Lillian J. Ratliff, Vijay Gupta, Thulasi Mylvaganam
2024	A	`conf`	Near-Optimal Pure Exploration in Matrix Games: A Generalization of Stochastic Bandits & Dueling Bandits. AISTATS Arnab Maiti, Ross Boczar, Kevin Jamieson, Lillian J. Ratliff
2024	J	`jnl`	Principal-Agent Bandit Games with Self-Interested and Exploratory Learning Agents. CoRR Junyan Liu, Lillian J. Ratliff
2024	A*	`conf`	Sample Complexity Reduction via Policy Difference Estimation in Tabular Reinforcement Learning. NeurIPS Adhyyan Narang, Andrew Wagenmaker, Lillian J. Ratliff, Kevin Jamieson
2024	J	`jnl`	Sample Complexity Reduction via Policy Difference Estimation in Tabular Reinforcement Learning. CoRR Adhyyan Narang, Andrew Wagenmaker, Lillian J. Ratliff, Kevin Jamieson
2023	J	`jnl`	Adaptive constraint satisfaction for Markov decision process congestion games: Application to transportation networks. Autom. Sarah H. Q. Li, Yue Yu, Nicolas I. Miguel, Daniel J. Calderone, Lillian J. Ratliff, Behçet Açikmese
2023	A	`conf`	Approximate Regions of Attraction in Learning with Decision-Dependent Distributions. AISTATS Roy Dong, Heling Zhang, Lillian J. Ratliff
2023	J	`jnl`	Consistent Conjectural Variations Equilibria: Characterization and Stability for a Class of Continuous Games. IEEE Control. Syst. Lett. Daniel J. Calderone, Benjamin J. Chasnov, Samuel A. Burden, Lillian J. Ratliff
2023	J	`jnl`	Consistent Conjectural Variations Equilibrium: Characterization & Stability for a Class of Continuous Games. CoRR Daniel J. Calderone, Benjamin J. Chasnov, Samuel A. Burden, Lillian J. Ratliff
2023	J	`jnl`	Convergent First-Order Methods for Bi-level Optimization and Stackelberg Games. CoRR Chinmay Maheshwari, S. Shankar Sastry, Lillian J. Ratliff, Eric Mazumdar
2023	J	`jnl`	Coupled Gradient Flows for Strategic Non-Local Distribution Shift. CoRR Lauren E. Conger, Franca Hoffmann, Eric Mazumdar, Lillian J. Ratliff
2023	J	`jnl`	Human adaptation to adaptive machines converges to game-theoretic equilibria. CoRR Benjamin J. Chasnov, Lillian J. Ratliff, Samuel A. Burden
2023	J	`jnl`	Initializing Services in Interactive ML Systems for Diverse Users. CoRR Avinandan Bose, Mihaela Curmei, Daniel L. Jiang, Jamie Morgenstern, Sarah Dean, Lillian J. Ratliff, Maryam Fazel
2023	A	`conf`	Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games. AISTATS Arnab Maiti, Kevin Jamieson, Lillian J. Ratliff
2023	J	`jnl`	Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games. CoRR Arnab Maiti, Kevin Jamieson, Lillian J. Ratliff
2023	J	`jnl`	Logarithmic Regret for Matrix Games against an Adversary with Noisy Bandit Feedback. CoRR Arnab Maiti, Kevin Jamieson, Lillian J. Ratliff
2023	J	`jnl`	Multiplayer Performative Prediction: Learning in Decision-Dependent Games. J. Mach. Learn. Res. Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff
2023	J	`jnl`	Near-Optimal Pure Exploration in Matrix Games: A Generalization of Stochastic Bandits & Dueling Bandits. CoRR Arnab Maiti, Ross Boczar, Kevin Jamieson, Lillian J. Ratliff
2023	J	`jnl`	Query-Efficient Algorithms to Find the Unique Nash Equilibrium in a Two-Player Zero-Sum Matrix Game. CoRR Arnab Maiti, Ross Boczar, Kevin Jamieson, Lillian J. Ratliff
2023	A*	`conf`	Stackelberg Games for Learning Emergent Behaviors During Competitive Autocurricula. ICRA Boling Yang, Liyuan Zheng, Lillian J. Ratliff, Byron Boots, Joshua R. Smith
2023	J	`jnl`	Stackelberg Games for Learning Emergent Behaviors During Competitive Autocurricula. CoRR Boling Yang, Liyuan Zheng, Lillian J. Ratliff, Byron Boots, Joshua R. Smith
2023	A*	`conf`	Strategic Distribution Shift of Interacting Agents via Coupled Gradient Flows. NeurIPS Lauren E. Conger, Franca Hoffmann, Eric Mazumdar, Lillian J. Ratliff
2022	A*	`conf`	Decision-Dependent Risk Minimization in Geometrically Decaying Dynamic Environments. AAAI Mitas Ray, Lillian J. Ratliff, Dmitriy Drusvyatskiy, Maryam Fazel
2022	J	`jnl`	Decision-Dependent Risk Minimization in Geometrically Decaying Dynamic Environments. CoRR Mitas Ray, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff
2022	B	`conf`	Fast Convergence of Optimistic Gradient Ascent in Network Zero-Sum Extensive Form Games. SAGT Georgios Piliouras, Lillian J. Ratliff, Ryann Sim, Stratis Skoulakis
2022	J	`jnl`	Fast Convergence of Optimistic Gradient Ascent in Network Zero-Sum Extensive Form Games. CoRR Georgios Piliouras, Lillian J. Ratliff, Ryann Sim, Stratis Skoulakis
2022	J	`jnl`	General sum stochastic games with networked information flows. CoRR Sarah H. Q. Li, Lillian J. Ratliff, Peeyush Kumar
2022	—	`conf`	Improved Rates for Derivative Free Gradient Play in Strongly Monotone Games CDC Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff
2022	A*	`conf`	Instance-optimal PAC Algorithms for Contextual Bandits. NeurIPS Zhaoqi Li, Lillian J. Ratliff, Houssam Nassif, Kevin Jamieson, Lalit Jain
2022	J	`jnl`	Instance-optimal PAC Algorithms for Contextual Bandits. CoRR Zhaoqi Li, Lillian J. Ratliff, Houssam Nassif, Kevin Jamieson, Lalit Jain
2022	J	`jnl`	Interactive Combinatorial Bandits: Balancing Competitivity and Complementarity. CoRR Adhyyan Narang, Omid Sadeghi, Lillian J. Ratliff, Maryam Fazel, Jeff A. Bilmes
2022	J	`jnl`	Koopman Operator Applications in Signalized Traffic Systems. IEEE Trans. Intell. Transp. Syst. Esther Ling, Liyuan Zheng, Lillian J. Ratliff, Samuel Coogan
2022	A	`conf`	Learning in Stochastic Monotone Games with Decision-Dependent Data. AISTATS Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff
2022	A*	`conf`	Minimax Optimization with Smooth Algorithmic Adversaries. ICLR Tanner Fiez, Chi Jin, Praneeth Netrapalli, Lillian J. Ratliff
2022	J	`jnl`	Multi-learner risk reduction under endogenous participation dynamics. CoRR Sarah Dean, Mihaela Curmei, Lillian J. Ratliff, Jamie Morgenstern, Maryam Fazel
2022	J	`jnl`	Multiplayer Performative Prediction: Learning in Decision-Dependent Games. CoRR Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, 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
2022	J	`jnl`	Variable demand and multi-commodity flow in Markovian network equilibrium. Autom. Yue Yu, Daniel J. Calderone, Sarah H. Q. Li, Lillian J. Ratliff, Behçet Açikmese
2022	A	`conf`	Zeroth-Order Methods for Convex-Concave Min-max Problems: Applications to Decision-Dependent Risk Minimization. AISTATS Chinmay Maheshwari, Chih-Yuan Chiu, Eric Mazumdar, Shankar Sastry, Lillian J. Ratliff
2021	J	`jnl`	Adaptive Incentive Design. IEEE Trans. Autom. Control. Lillian J. Ratliff, Tanner Fiez
2021	J	`jnl`	Disturbance Decoupling for Gradient-Based Multi-Agent Learning With Quadratic Costs. IEEE Control. Syst. Lett. Sarah H. Q. Li, Lillian J. Ratliff, Behçet Açikmese
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	J	`jnl`	Improved rates for derivative free play in convex games. CoRR Dmitriy Drusvyatskiy, Lillian J. Ratliff
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	—	`conf`	Safe Reinforcement Learning of Control-Affine Systems with Vertex Networks. L4DC Liyuan Zheng, Yuanyuan Shi, Lillian J. Ratliff, Baosen Zhang
2021	J	`jnl`	Stackelberg Actor-Critic: Game-Theoretic Reinforcement Learning Algorithms. CoRR Liyuan Zheng, Tanner Fiez, Zane Alumbaugh, Benjamin Chasnov, Lillian J. Ratliff
2021	J	`jnl`	Which Echo Chamber? Regions of Attraction in Learning with Decision-Dependent Distributions. CoRR Roy Dong, Lillian J. Ratliff
2021	J	`jnl`	Zeroth-Order Methods for Convex-Concave Minmax Problems: Applications to Decision-Dependent Risk Minimization. CoRR Chinmay Maheshwari, Chih-Yuan Chiu, Eric Mazumdar, S. Shankar Sastry, 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`	Competitive Statistical Estimation With Strategic Data Sources. IEEE Trans. Autom. Control. Tyler Westenbroek, Roy Dong, Lillian J. Ratliff, S. Shankar Sastry
2020	—	`conf`	Constrained Upper Confidence Reinforcement Learning. L4DC Liyuan Zheng, Lillian J. Ratliff
2020	J	`jnl`	Constrained Upper Confidence Reinforcement Learning. CoRR Liyuan Zheng, Lillian J. Ratliff
2020	J	`jnl`	Disturbance Decoupling for Gradient-based Multi-Agent Learning with Quadratic Costs. CoRR Sarah H. Q. Li, Lillian J. Ratliff, Behçet Açikmese
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`	Function Design for Improved Competitive Ratio in Online Resource Allocation with Procurement Costs. CoRR Mitas Ray, Omid Sadeghi, Lillian J. Ratliff, Maryam Fazel
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
2020	J	`jnl`	Inverse Risk-Sensitive Reinforcement Learning. IEEE Trans. Autom. Control. Lillian J. Ratliff, Eric Mazumdar
2020	J	`jnl`	Local Nash Equilibria are Isolated, Strict Local Nash Equilibria in 'Almost All' Zero-Sum Continuous Games. CoRR Eric Mazumdar, Lillian J. Ratliff
2020	J	`jnl`	Modeling Curbside Parking as a Network of Finite Capacity Queues. IEEE Trans. Intell. Transp. Syst. Chase P. Dowling, Lillian J. Ratliff, Baosen Zhang
2020	J	`jnl`	On Gradient-Based Learning in Continuous Games. SIAM J. Math. Data Sci. Eric Mazumdar, Lillian J. Ratliff, S. Shankar Sastry
2020	A	`conf`	Policy-Gradient Algorithms Have No Guarantees of Convergence in Linear Quadratic Games. AAMAS Eric Mazumdar, Lillian J. Ratliff, Michael I. Jordan, S. Shankar Sastry
2020	J	`jnl`	Safe Reinforcement Learning of Control-Affine Systems with Vertex Networks. CoRR Liyuan Zheng, Yuanyuan Shi, Lillian J. Ratliff, Baosen Zhang
2020	—	`conf`	Stability of Gradient Learning Dynamics in Continuous Games: Scalar Action Spaces. CDC Benjamin J. Chasnov, Daniel J. Calderone, Behçet Açikmese, Samuel A. Burden, Lillian J. Ratliff
2020	J	`jnl`	Stability of Gradient Learning Dynamics in Continuous Games: Scalar Action Spaces. CoRR Benjamin J. Chasnov, Daniel J. Calderone, Behçet Açikmese, Samuel A. Burden, Lillian J. Ratliff
2020	J	`jnl`	Stability of Gradient Learning Dynamics in Continuous Games: Vector Action Spaces. CoRR Benjamin J. Chasnov, Daniel J. Calderone, Behçet Açikmese, Samuel A. Burden, Lillian J. Ratliff
2020	J	`jnl`	Uncertainty in Multicommodity Routing Networks: When Does It Help? IEEE Trans. Autom. Control. Shreyas Sekar, Liyuan Zheng, Lillian J. Ratliff, Baosen Zhang
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`	Competitive Statistical Estimation with Strategic Data Sources. CoRR Tyler Westenbroek, Roy Dong, Lillian J. Ratliff, S. Shankar Sastry
2019	A	`conf`	Convergence Analysis of Gradient-Based Learning in Continuous Games. UAI Benjamin Chasnov, Lillian J. Ratliff, Eric Mazumdar, Samuel Burden
2019	J	`jnl`	Convergence Analysis of Gradient-Based Learning with Non-Uniform Learning Rates in Non-Cooperative Multi-Agent Settings. CoRR Benjamin Chasnov, Lillian J. Ratliff, Eric Mazumdar, Samuel A. Burden
2019	J	`jnl`	Convergence of Learning Dynamics in Stackelberg Games. CoRR Tanner Fiez, Benjamin Chasnov, Lillian J. Ratliff
2019	—	`conf`	Distributed Learning in Network Games: a Dual Averaging Approach. CDC Shahriar Talebi, Siavash Alemzadeh, Lillian J. Ratliff, Mehran Mesbahi
2019	J	`jnl`	Global Convergence of Policy Gradient for Sequential Zero-Sum Linear Quadratic Dynamic Games. CoRR Jingjing Bu, Lillian J. Ratliff, Mehran Mesbahi
2019	—	`conf`	Incentive Design for Temporal Logic Objectives. CDC Yagiz Savas, Vijay Gupta, Melkior Ornik, Lillian J. Ratliff, Ufuk Topcu
2019	—	`conf`	Local Nash Equilibria are Isolated, Strict Local Nash Equilibria in 'Almost All' Zero-Sum Continuous Games. CDC Eric Mazumdar, Lillian J. Ratliff
2019	B	`conf`	Mobilytics-Gym: A Simulation Framework for Analyzing Urban Mobility Decision Strategies. SMARTCOMP Chinmaya Samal, Abhishek Dubey, Lillian J. Ratliff
2019	—	`conf`	Multi-Dimensional Continuous Type Population Potential Games. CDC Daniel J. Calderone, Lillian J. Ratliff
2019	J	`jnl`	Online Constraint Satisfaction via Tolls in MDP Congestion Games. CoRR Sarah H. Q. Li, Yue Yu, Daniel J. Calderone, Lillian J. Ratliff, Behçet Açikmese
2019	J	`jnl`	Policy-Gradient Algorithms Have No Guarantees of Convergence in Continuous Action and State Multi-Agent Settings. CoRR Eric Mazumdar, Lillian J. Ratliff, Michael I. Jordan, S. Shankar Sastry
2019	—	`conf`	Sensitivity Analysis for Markov Decision Process Congestion Games. CDC Sarah H. Q. Li, Daniel J. Calderone, Lillian J. Ratliff, Behçet Açikmese
2019	J	`jnl`	Sensitivity Analysis for Markov Decision Process Congestion Games. CoRR Sarah H. Q. Li, Daniel J. Calderone, Lillian J. Ratliff, Behçet Açikmese
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
2019	C	`conf`	Tolling for Constraint Satisfaction in Markov Decision Process Congestion Games. ACC Sarah H. Q. Li, Yue Yu, Daniel J. Calderone, Lillian J. Ratliff, Behçet Açikmese
2019	J	`jnl`	Tolling for Constraint Satisfaction in Markov Decision Process Congestion Games. CoRR Sarah H. Q. Li, Yue Yu, Daniel J. Calderone, Lillian J. Ratliff, Behçet Açikmese
2018	J	`jnl`	A Robust Utility Learning Framework via Inverse Optimization. IEEE Trans. Control. Syst. Technol. Ioannis C. Konstantakopoulos, Lillian J. Ratliff, Ming Jin, S. Shankar Sastry, Costas J. Spanos
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
2018	—	`conf`	Koopman Operator Approach for Instability Detection and Mitigation in Signalized Traffic. ITSC Esther Ling, Lillian J. Ratliff, Samuel Coogan
2018	B	`conf`	Mobilytics- An Extensible, Modular and Resilient Mobility Platform. SMARTCOMP Chinmaya Samal, Abhishek Dubey, Lillian J. Ratliff
2018	J	`jnl`	On the Convergence of Competitive, Multi-Agent Gradient-Based Learning. CoRR Eric Mazumdar, Lillian J. Ratliff
2018	J	`jnl`	Quantifying the Utility-Privacy Tradeoff in the Internet of Things. ACM Trans. Cyber Phys. Syst. Roy Dong, Lillian J. Ratliff, Alvaro A. Cárdenas, Henrik Ohlsson, S. Shankar Sastry
2018	J	`jnl`	Towards a Socially Optimal Multi-Modal Routing Platform. CoRR Chinmaya Samal, Liyuan Zheng, Fangzhou Sun, Lillian J. Ratliff, Abhishek Dubey
2018	C	`conf`	Uncertainty in Multi-Commodity Routing Networks: When does it help? ACC Shreyas Sekar, Liyuan Zheng, Lillian J. Ratliff, Baosen Zhang
2017	J	`jnl`	A Robust Utility Learning Framework via Inverse Optimization. CoRR Ioannis C. Konstantakopoulos, Lillian J. Ratliff, Ming Jin, S. Shankar Sastry, Costas J. Spanos
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`	Learning prospect theory value function and reference point of a sequential decision maker. CDC Kamil Nar, Lillian J. Ratliff, Shankar Sastry
2017	C	`conf`	Leveraging correlations in utility learning. ACC Ioannis C. Konstantakopoulos, Lillian J. Ratliff, Ming Jin, Costas J. Spanos
2017	—	`conf`	Optimizing curbside parking resources subject to congestion constraints. CDC Chase Dowling, Tanner Fiez, Lillian J. Ratliff, Baosen Zhang
2017	J	`jnl`	Risk-Sensitive Inverse Reinforcement Learning via Gradient Methods. CoRR Lillian J. Ratliff, Eric Mazumdar
2017	J	`jnl`	Statistical Estimation with Strategic Data Sources in Competitive Settings. CoRR Tyler Westenbroek, Roy Dong, Lillian J. Ratliff, S. Shankar Sastry
2017	—	`conf`	Statistical estimation with strategic data sources in competitive settings. CDC Tyler Westenbroek, Roy Dong, Lillian J. Ratliff, S. Shankar Sastry
2017	J	`jnl`	Uncertainty in Multi-Commodity Routing Networks: When does it help? CoRR Shreyas Sekar, Liyuan Zheng, Lillian J. Ratliff, Baosen Zhang
2016	—	`conf`	Inverse modeling of non-cooperative agents via mixture of utilities. CDC Ioannis C. Konstantakopoulos, Lillian J. Ratliff, Ming Jin, Costas J. Spanos, S. Shankar Sastry
2016	J	`jnl`	On the Characterization of Local Nash Equilibria in Continuous Games. IEEE Trans. Autom. Control. Lillian J. Ratliff, Samuel A. Burden, S. Shankar Sastry
2016	J	`jnl`	To Observe or Not to Observe: Queuing Game Framework for Urban Parking. CoRR Lillian J. Ratliff, Chase Dowling, Eric Mazumdar, Baosen Zhang
2016	—	`conf`	To observe or not to observe: Queuing game framework for urban parking. CDC Lillian J. Ratliff, Chase Dowling, Eric Mazumdar, Baosen Zhang
2016	—	`conf`	Understanding the impact of parking on urban mobility via routing games on queue-flow networks. CDC Daniel J. Calderone, Eric Mazumdar, Lillian J. Ratliff, S. Shankar Sastry
2015	—	`conf`	Lane pricing via decision-theoretic lane changing model of driver behavior. CDC Daniel J. Calderone, Lillian J. Ratliff, S. Shankar Sastry
2015	—	`conf`	Nuclear norm minimization for blind subspace identification (N2BSID). CDC Dexter Scobee, Lillian J. Ratliff, Roy Dong, Henrik Ohlsson, Michel Verhaegen, S. Shankar Sastry
2015	—	`conf`	REST: a reliable estimation of stopping time algorithm for social game experiments. ICCPS Ming Jin, Lillian J. Ratliff, Ioannis C. Konstantakopoulos, Costas J. Spanos, Shankar Sastry
2014	J	`jnl`	Analysis of the Godunov-Based Hybrid Model for Ramp Metering and Robust Feedback Control Design. IEEE Trans. Intell. Transp. Syst. Pushkin Kachroo, Lillian J. Ratliff, Shankar Sastry
2014	J	`jnl`	Effects of Risk on Privacy Contracts for Demand-Side Management. CoRR Lillian J. Ratliff, Carlos A. Barreto, Roy Dong, Henrik Ohlsson, Alvaro A. Cárdenas, S. Shankar Sastry
2014	—	`conf`	Energy efficiency via incentive design and utility learning. HiCoNS Lillian J. Ratliff, Roy Dong, Henrik Ohlsson, S. Shankar Sastry
2014	—	`conf`	Fundamental limits of nonintrusive load monitoring. HiCoNS Roy Dong, Lillian J. Ratliff, Henrik Ohlsson, S. Shankar Sastry
2014	C	`conf`	Genericity and structural stability of non-degenerate differential Nash equilibria. ACC Lillian J. Ratliff, Samuel A. Burden, S. Shankar Sastry
2014	—	`conf`	Privacy and customer segmentation in the smart grid. CDC Lillian J. Ratliff, Roy Dong, Henrik Ohlsson, Alvaro A. Cárdenas, S. Shankar Sastry
2014	J	`jnl`	Quantifying the Utility-Privacy Tradeoff in the Smart Grid. CoRR Roy Dong, Alvaro A. Cárdenas, Lillian J. Ratliff, Henrik Ohlsson, S. Shankar Sastry
2014	J	`jnl`	Social Game for Building Energy Efficiency: Utility Learning, Simulation, and Analysis. CoRR Ioannis C. Konstantakopoulos, Lillian J. Ratliff, Ming Jin, S. Shankar Sastry, Costas J. Spanos
2014	—	`conf`	Social game for building energy efficiency: Incentive design. Allerton Lillian J. Ratliff, Ming Jin, Ioannis C. Konstantakopoulos, Costas J. Spanos, S. Shankar Sastry
2013	—	`conf`	A dynamical systems approach to energy disaggregation. CDC Roy Dong, Lillian J. Ratliff, Henrik Ohlsson, S. Shankar Sastry
2013	—	`conf`	An inverse correlated equilibrium framework for utility learning in multiplayer, noncooperative settings. HiCoNS Aaron M. Bestick, Lillian J. Ratliff, Posu Yan, Ruzena Bajcsy, S. Shankar Sastry
2013	J	`jnl`	Behavior Modification and Utility Learning via Energy Disaggregation. CoRR Lillian J. Ratliff, Roy Dong, Henrik Ohlsson, S. Shankar Sastry
2013	J	`jnl`	Blind Identification of ARX Models with Piecewise Constant Inputs CoRR Henrik Ohlsson, Lillian J. Ratliff, Roy Dong, S. Shankar Sastry
2013	J	`jnl`	Blind Identification via Lifting. CoRR Henrik Ohlsson, Lillian J. Ratliff, Roy Dong, S. Shankar Sastry
2013	—	`conf`	Characterization and computation of local Nash equilibria in continuous games. Allerton Lillian J. Ratliff, Samuel Burden, S. Shankar Sastry
2013	—	`conf`	Energy disaggregation via adaptive filtering. Allerton Roy Dong, Lillian J. Ratliff, Henrik Ohlsson, S. Shankar Sastry
2013	C	`conf`	Energy management via pricing in LQ dynamic games. ACC Samuel Coogan, Lillian J. Ratliff, Daniel J. Calderone, Claire J. Tomlin, S. Shankar Sastry
2013	—	`conf`	Pricing design for robustness in linear quadratic games. CDC Daniel J. Calderone, Lillian J. Ratliff, S. Shankar Sastry
2012	—	`conf`	Pricing in linear-quadratic dynamic games. Allerton Conference Lillian J. Ratliff, Samuel Coogan, Daniel J. Calderone, S. Shankar Sastry