Fridovich-Keil, David

10 publications

TMLR 2026 A Multi-Fidelity Control Variate Approach for Policy Gradient Estimation Xinjie Liu, Cyrus Neary, Kushagra Gupta, Wesley A. Suttle, Christian Ellis, Ufuk Topcu, David Fridovich-Keil
TMLR 2025 A Framework for Finding Local Saddle Points in Two-Player Zero-Sum Black-Box Games Shubhankar Agarwal, Hamzah I Khan, Sandeep P. Chinchali, David Fridovich-Keil
NeurIPS 2025 Cooperative Bargaining Games Without Utilities: Mediated Solutions from Direction Oracles Kushagra Gupta, Surya Murthy, Mustafa O. Karabag, Ufuk Topcu, David Fridovich-Keil
L4DC 2025 Dense Dynamics-Aware Reward Synthesis: Integrating Prior Experience with Demonstrations Cevahir Koprulu, Po-Han Li, Tianyu Qiu, Ruihan Zhao, Tyler Westenbroek, David Fridovich-Keil, Sandeep Chinchali, Ufuk Topcu
TMLR 2025 Real-Time Privacy Preservation for Robot Visual Perception Minkyu Choi, Yunhao Yang, Neel P. Bhatt, Kushagra Gupta, Sahil Shah, Aditya Rai, David Fridovich-Keil, Ufuk Topcu, Sandeep P. Chinchali
ICML 2025 Stealing That Free Lunch: Exposing the Limits of Dyna-Style Reinforcement Learning Brett Barkley, David Fridovich-Keil
L4DC 2024 An Investigation of Time Reversal Symmetry in Reinforcement Learning Brett Barkley, Amy Zhang, David Fridovich-Keil
CoRL 2024 Learning to Walk from Three Minutes of Real-World Data with Semi-Structured Dynamics Models Jacob Levy, Tyler Westenbroek, David Fridovich-Keil
CoRL 2023 Enabling Efficient, Reliable Real-World Reinforcement Learning with Approximate Physics-Based Models Tyler Westenbroek, Jacob Levy, David Fridovich-Keil
NeurIPS 2017 Fully Decentralized Policies for Multi-Agent Systems: An Information Theoretic Approach Roel Dobbe, David Fridovich-Keil, Claire Tomlin