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Kavosh Asadi

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TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models

Oct 09, 2023
Zuxin Liu, Jesse Zhang, Kavosh Asadi, Yao Liu, Ding Zhao, Shoham Sabach, Rasool Fakoor

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Resetting the Optimizer in Deep RL: An Empirical Study

Jun 30, 2023
Kavosh Asadi, Rasool Fakoor, Shoham Sabach

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TD Convergence: An Optimization Perspective

Jun 30, 2023
Kavosh Asadi, Shoham Sabach, Yao Liu, Omer Gottesman, Rasool Fakoor

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Characterizing the Action-Generalization Gap in Deep Q-Learning

May 11, 2022
Zhiyuan Zhou, Cameron Allen, Kavosh Asadi, George Konidaris

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Deep Q-Network with Proximal Iteration

Dec 10, 2021
Kavosh Asadi, Rasool Fakoor, Omer Gottesman, Michael L. Littman, Alexander J. Smola

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Coarse-Grained Smoothness for RL in Metric Spaces

Oct 23, 2021
Omer Gottesman, Kavosh Asadi, Cameron Allen, Sam Lobel, George Konidaris, Michael Littman

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Convergence of a Human-in-the-Loop Policy-Gradient Algorithm With Eligibility Trace Under Reward, Policy, and Advantage Feedback

Sep 15, 2021
Ishaan Shah, David Halpern, Kavosh Asadi, Michael L. Littman

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Learning State Abstractions for Transfer in Continuous Control

Feb 08, 2020
Kavosh Asadi, David Abel, Michael L. Littman

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Deep RBF Value Functions for Continuous Control

Feb 05, 2020
Kavosh Asadi, Ronald E. Parr, George D. Konidaris, Michael L. Littman

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Lipschitz Lifelong Reinforcement Learning

Jan 17, 2020
Erwan Lecarpentier, David Abel, Kavosh Asadi, Yuu Jinnai, Emmanuel Rachelson, Michael L. Littman

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