Kavosh Asadi

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 35

Top Topics

Reinforcement Learning

Lipschitz Continuity

Top Venues

Publications

Zuxin Liu, Jesse Zhang, Kavosh Asadi, Yao Liu, Ding Zhao, Shoham Sabach, Rasool Fakoor
TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models. ICLR (2024)
Kavosh Asadi, Yao Liu, Shoham Sabach, Ming Yin, Rasool Fakoor
Learning the Target Network in Function Space. CoRR (2024)
Omer Gottesman, Kavosh Asadi, Cameron S. Allen, Samuel Lobel, George Konidaris, Michael L. Littman
Coarse-Grained Smoothness for Reinforcement Learning in Metric Spaces. AISTATS (2023)
Kavosh Asadi, Shoham Sabach, Yao Liu, Omer Gottesman, Rasool Fakoor
TD Convergence: An Optimization Perspective. CoRR (2023)
Kavosh Asadi, Shoham Sabach, Yao Liu, Omer Gottesman, Rasool Fakoor
TD Convergence: An Optimization Perspective. NeurIPS (2023)
Zuxin Liu, Jesse Zhang, Kavosh Asadi, Yao Liu, Ding Zhao, Shoham Sabach, Rasool Fakoor
TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models. CoRR (2023)
Kavosh Asadi, Rasool Fakoor, Shoham Sabach
Resetting the Optimizer in Deep RL: An Empirical Study. CoRR (2023)
Kavosh Asadi, Rasool Fakoor, Shoham Sabach
Resetting the Optimizer in Deep RL: An Empirical Study. NeurIPS (2023)
Kavosh Asadi, Rasool Fakoor, Omer Gottesman, Taesup Kim, Michael L. Littman, Alexander J. Smola
Faster Deep Reinforcement Learning with Slower Online Network. NeurIPS (2022)
Zhiyuan Zhou, Cameron Allen, Kavosh Asadi, George Konidaris
Characterizing the Action-Generalization Gap in Deep Q-Learning. CoRR (2022)
Martin Klissarov, Rasool Fakoor, Jonas W. Mueller, Kavosh Asadi, Taesup Kim, Alexander J. Smola
Adaptive Interest for Emphatic Reinforcement Learning. NeurIPS (2022)
Kavosh Asadi, Rasool Fakoor, Omer Gottesman, Michael L. Littman, Alexander J. Smola
Deep Q-Network with Proximal Iteration. CoRR (2021)
Erwan Lecarpentier, David Abel, Kavosh Asadi, Yuu Jinnai, Emmanuel Rachelson, Michael L. Littman
Lipschitz Lifelong Reinforcement Learning. AAAI (2021)
Rasool Fakoor, Jonas Mueller, Kavosh Asadi, Pratik Chaudhari, Alexander J. Smola
Continuous Doubly Constrained Batch Reinforcement Learning. NeurIPS (2021)
Kavosh Asadi, Neev Parikh, Ronald E. Parr, George Dimitri Konidaris, Michael L. Littman
Deep Radial-Basis Value Functions for Continuous Control. AAAI (2021)
Omer Gottesman, Kavosh Asadi, Cameron Allen, Sam Lobel, George Konidaris, Michael L. Littman
Coarse-Grained Smoothness for RL in Metric Spaces. CoRR (2021)
Ishaan Shah, David Halpern, Kavosh Asadi, Michael L. Littman
Convergence of a Human-in-the-Loop Policy-Gradient Algorithm With Eligibility Trace Under Reward, Policy, and Advantage Feedback. CoRR (2021)
Kavosh Asadi, Ronald E. Parr, George Dimitri Konidaris, Michael L. Littman
Deep RBF Value Functions for Continuous Control. CoRR (2020)
Erwan Lecarpentier, David Abel, Kavosh Asadi, Yuu Jinnai, Emmanuel Rachelson, Michael L. Littman
Lipschitz Lifelong Reinforcement Learning. CoRR (2020)
Kavosh Asadi, David Abel, Michael L. Littman
Learning State Abstractions for Transfer in Continuous Control. CoRR (2020)
Kavosh Asadi, Dipendra Misra, Seungchan Kim, Michael L. Littman
Combating the Compounding-Error Problem with a Multi-step Model. CoRR (2019)
David Abel, Dilip Arumugam, Kavosh Asadi, Yuu Jinnai, Michael L. Littman, Lawson L. S. Wong
State Abstraction as Compression in Apprenticeship Learning. AAAI (2019)
Seungchan Kim, Kavosh Asadi, Michael L. Littman, George Dimitri Konidaris
DeepMellow: Removing the Need for a Target Network in Deep Q-Learning. IJCAI (2019)
Seungchan Kim, Kavosh Asadi, Michael L. Littman, George Dimitri Konidaris
Removing the Target Network from Deep Q-Networks with the Mellowmax Operator. AAMAS (2019)
Kavosh Asadi, Evan Cater, Dipendra Misra, Michael L. Littman
Towards a Simple Approach to Multi-step Model-based Reinforcement Learning. CoRR (2018)
Dilip Arumugam, David Abel, Kavosh Asadi, Nakul Gopalan, Christopher Grimm, Jun Ki Lee, Lucas Lehnert, Michael L. Littman
Mitigating Planner Overfitting in Model-Based Reinforcement Learning. CoRR (2018)
Kavosh Asadi, Dipendra Misra, Michael L. Littman
Lipschitz Continuity in Model-based Reinforcement Learning. ICML (2018)
Kavosh Asadi, Dipendra Misra, Michael L. Littman
Lipschitz Continuity in Model-based Reinforcement Learning. CoRR (2018)
Kavosh Asadi, Evan Cater, Dipendra Misra, Michael L. Littman
Equivalence Between Wasserstein and Value-Aware Model-based Reinforcement Learning. CoRR (2018)
Kavosh Asadi, Michael L. Littman
An Alternative Softmax Operator for Reinforcement Learning. ICML (2017)
Jason D. Williams, Kavosh Asadi, Geoffrey Zweig
Hybrid Code Networks: practical and efficient end-to-end dialog control with supervised and reinforcement learning. CoRR (2017)
Kavosh Asadi, Cameron Allen, Melrose Roderick, Abdel-rahman Mohamed, George Dimitri Konidaris, Michael L. Littman
Mean Actor Critic. CoRR (2017)
Jason D. Williams, Kavosh Asadi, Geoffrey Zweig
Hybrid Code Networks: practical and efficient end-to-end dialog control with supervised and reinforcement learning. ACL (1) (2017)
Kavosh Asadi, Jason D. Williams
Sample-efficient Deep Reinforcement Learning for Dialog Control. CoRR (2016)
Kavosh Asadi, Michael L. Littman
A New Softmax Operator for Reinforcement Learning. CoRR (2016)