Wagenmaker, Andrew

15 publications

ICML 2025 Behavioral Exploration: Learning to Explore via In-Context Adaptation Andrew Wagenmaker, Zhiyuan Zhou, Sergey Levine

CoRL 2025 Steering Your Diffusion Policy with Latent Space Reinforcement Learning Andrew Wagenmaker, Yunchu Zhang, Mitsuhiko Nakamoto, Seohong Park, Waleed Yagoub, Anusha Nagabandi, Abhishek Gupta, Sergey Levine

ICLR 2024 ASID: Active Exploration for System Identification in Robotic Manipulation Marius Memmel, Andrew Wagenmaker, Chuning Zhu, Dieter Fox, Abhishek Gupta

NeurIPS 2024 Active Learning of Neural Population Dynamics Using Two-Photon Holographic Optogenetics Andrew Wagenmaker, Lu Mi, Marton Rozsa, Matthew S. Bull, Karel Svoboda, Kayvon Daie, Matthew D. Golub, Kevin Jamieson

NeurIPS 2024 Corruption-Robust Linear Bandits: Minimax Optimality and Gap-Dependent Misspecification Haolin Liu, Artin Tajdini, Andrew Wagenmaker, Chen-Yu Wei

UAI 2024 Fair Active Learning in Low-Data Regimes Romain Camilleri, Andrew Wagenmaker, Jamie Morgenstern, Lalit Jain, Kevin Jamieson

NeurIPS 2024 Humor in AI: Massive Scale Crowd-Sourced Preferences and Benchmarks for Cartoon Captioning Jifan Zhang, Lalit Jain, Yang Guo, Jiayi Chen, Kuan Lok Zhou, Siddharth Suresh, Andrew Wagenmaker, Scott Sievert, Timothy Rogers, Kevin Jamieson, Robert Mankoff, Robert Nowak

NeurIPS 2024 Overcoming the Sim-to-Real Gap: Leveraging Simulation to Learn to Explore for Real-World RL Andrew Wagenmaker, Kevin Huang, Liyiming Ke, Kevin Jamieson, Abhishek Gupta

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

ICML 2023 Leveraging Offline Data in Online Reinforcement Learning Andrew Wagenmaker, Aldo Pacchiano

NeurIPS 2023 Optimal Exploration for Model-Based RL in Nonlinear Systems Andrew Wagenmaker, Guanya Shi, Kevin G. Jamieson

NeurIPS 2022 Active Learning with Safety Constraints Romain Camilleri, Andrew Wagenmaker, Jamie H Morgenstern, Lalit Jain, Kevin G. Jamieson

NeurIPS 2022 Instance-Dependent Near-Optimal Policy Identification in Linear MDPs via Online Experiment Design Andrew Wagenmaker, Kevin G. Jamieson

AISTATS 2021 Experimental Design for Regret Minimization in Linear Bandits Andrew Wagenmaker, Julian Katz-Samuels, Kevin Jamieson

COLT 2020 Active Learning for Identification of Linear Dynamical Systems Andrew Wagenmaker, Kevin Jamieson