Kavosh Asadi - RankMe

47 papers A* 13A 2Journal 30Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	$$\texttt{C2-DPO}$$: Constrained Controlled Direct Preference Optimization. Trans. Mach. Learn. Res. Kavosh Asadi, Xingzi Xu, Julien Han, Ege Beyazit, Idan Pipano, Dominique Perrault-Joncas, Shoham Sabach, Mohammad Ghavamzadeh, Karim Bouyarmane
2026	J	`jnl`	Displacement-Resistant Extensions of DPO with Nonconvex CoRR Idan Pipano, Shoham Sabach, Kavosh Asadi, Mohammad Ghavamzadeh
2026	J	`jnl`	Generative Reasoning Re-ranker. CoRR Mingfu Liang, Yufei Li, Jay Xu, Kavosh Asadi, Xi Liu, Shuo Gu, Kaushik Rangadurai, Frank Shyu, Shuaiwen Wang, Song Yang, Zhijing Li, Jiang Liu, Mengying Sun, Fei Tian, Xiaohan Wei, Chonglin Sun, Jacob Tao, Shike Mei, Wenlin Chen, Santanu Kolay, Sandeep Pandey, Hamed Firooz, Luke Simon
2026	J	`jnl`	Structure Enables Effective Self-Localization of Errors in LLMs. CoRR Ankur Samanta, Akshayaa Magesh, Ayush Jain, Kavosh Asadi, Youliang Yu, Daniel Jiang, Boris Vidolov, Kaveh Hassani, Paul Sajda, Jalaj Bhandari, Yonathan Efroni
2025	J	`jnl`	Activation sharding for scalable training of large models. Trans. Mach. Learn. Res. Xingzi Xu, Amir Tavanaei, Kavosh Asadi, Karim Bouyarmane
2025	J	`jnl`	Adjoint sharding for very long context training of state space models. CoRR Xingzi Xu, Amir Tavanaei, Kavosh Asadi, Karim Bouyarmane
2025	J	`jnl`	C-3DPO: Constrained Controlled Classification for Direct Preference Optimization. CoRR Kavosh Asadi, Julien Han, Xingzi Xu, Dominique Perrault-Joncas, Shoham Sabach, Karim Bouyarmane, Mohammad Ghavamzadeh
2025	J	`jnl`	InstructVTON: Optimal Auto-Masking and Natural-Language-Guided Interactive Style Control for Inpainting-Based Virtual Try-On. CoRR Julien Han, Shuwen Qiu, Qi Li, Xingzi Xu, Mehmet Saygin Seyfioglu, Kavosh Asadi, Karim Bouyarmane
2025	J	`jnl`	Learning to Reason Efficiently with Discounted Reinforcement Learning. CoRR Alex Ayoub, Kavosh Asadi, Dale Schuurmans, Csaba Szepesvári, Karim Bouyarmane
2024	A*	`conf`	Learning the Target Network in Function Space. ICML Kavosh Asadi, Yao Liu, Shoham Sabach, Ming Yin, Rasool Fakoor
2024	J	`jnl`	Learning the Target Network in Function Space. CoRR Kavosh Asadi, Yao Liu, Shoham Sabach, Ming Yin, Rasool Fakoor
2024	J	`jnl`	On Welfare-Centric Fair Reinforcement Learning. RLJ Cyrus Cousins, Kavosh Asadi, Elita A. Lobo, Michael Littman
2024	A*	`conf`	TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models. ICLR Zuxin Liu, Jesse Zhang, Kavosh Asadi, Yao Liu, Ding Zhao, Shoham Sabach, Rasool Fakoor
2023	A	`conf`	Coarse-Grained Smoothness for Reinforcement Learning in Metric Spaces. AISTATS Omer Gottesman, Kavosh Asadi, Cameron S. Allen, Samuel Lobel, George Konidaris, Michael Littman
2023	A*	`conf`	Resetting the Optimizer in Deep RL: An Empirical Study. NeurIPS Kavosh Asadi, Rasool Fakoor, Shoham Sabach
2023	J	`jnl`	Resetting the Optimizer in Deep RL: An Empirical Study. CoRR Kavosh Asadi, Rasool Fakoor, Shoham Sabach
2023	J	`jnl`	TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models. CoRR Zuxin Liu, Jesse Zhang, Kavosh Asadi, Yao Liu, Ding Zhao, Shoham Sabach, Rasool Fakoor
2023	A*	`conf`	TD Convergence: An Optimization Perspective. NeurIPS Kavosh Asadi, Shoham Sabach, Yao Liu, Omer Gottesman, Rasool Fakoor
2023	J	`jnl`	TD Convergence: An Optimization Perspective. CoRR Kavosh Asadi, Shoham Sabach, Yao Liu, Omer Gottesman, Rasool Fakoor
2022	A*	`conf`	Adaptive Interest for Emphatic Reinforcement Learning. NeurIPS Martin Klissarov, Rasool Fakoor, Jonas W. Mueller, Kavosh Asadi, Taesup Kim, Alexander J. Smola
2022	J	`jnl`	Characterizing the Action-Generalization Gap in Deep Q-Learning. CoRR Zhiyuan Zhou, Cameron Allen, Kavosh Asadi, George Konidaris
2022	A*	`conf`	Faster Deep Reinforcement Learning with Slower Online Network. NeurIPS Kavosh Asadi, Rasool Fakoor, Omer Gottesman, Taesup Kim, Michael L. Littman, Alexander J. Smola
2021	J	`jnl`	Coarse-Grained Smoothness for RL in Metric Spaces. CoRR Omer Gottesman, Kavosh Asadi, Cameron Allen, Sam Lobel, George Konidaris, Michael Littman
2021	A*	`conf`	Continuous Doubly Constrained Batch Reinforcement Learning. NeurIPS Rasool Fakoor, Jonas Mueller, Kavosh Asadi, Pratik Chaudhari, Alexander J. Smola
2021	J	`jnl`	Convergence of a Human-in-the-Loop Policy-Gradient Algorithm With Eligibility Trace Under Reward, Policy, and Advantage Feedback. CoRR Ishaan Shah, David Halpern, Kavosh Asadi, Michael L. Littman
2021	J	`jnl`	Deep Q-Network with Proximal Iteration. CoRR Kavosh Asadi, Rasool Fakoor, Omer Gottesman, Michael L. Littman, Alexander J. Smola
2021	A*	`conf`	Deep Radial-Basis Value Functions for Continuous Control. AAAI Kavosh Asadi, Neev Parikh, Ronald E. Parr, George Dimitri Konidaris, Michael L. Littman
2021	A*	`conf`	Lipschitz Lifelong Reinforcement Learning. AAAI Erwan Lecarpentier, David Abel, Kavosh Asadi, Yuu Jinnai, Emmanuel Rachelson, Michael L. Littman
2021	—	`—`	Smoothness in Reinforcement Learning with Large State and Action Spaces. Kavosh Asadi
2020	J	`jnl`	Deep RBF Value Functions for Continuous Control. CoRR Kavosh Asadi, Ronald E. Parr, George Dimitri Konidaris, Michael L. Littman
2020	J	`jnl`	Learning State Abstractions for Transfer in Continuous Control. CoRR Kavosh Asadi, David Abel, Michael Littman
2020	J	`jnl`	Lipschitz Lifelong Reinforcement Learning. CoRR Erwan Lecarpentier, David Abel, Kavosh Asadi, Yuu Jinnai, Emmanuel Rachelson, Michael L. Littman
2019	J	`jnl`	Combating the Compounding-Error Problem with a Multi-step Model. CoRR Kavosh Asadi, Dipendra Misra, Seungchan Kim, Michael L. Littman
2019	A*	`conf`	DeepMellow: Removing the Need for a Target Network in Deep Q-Learning. IJCAI Seungchan Kim, Kavosh Asadi, Michael L. Littman, George Dimitri Konidaris
2019	A	`conf`	Removing the Target Network from Deep Q-Networks with the Mellowmax Operator. AAMAS Seungchan Kim, Kavosh Asadi, Michael L. Littman, George Dimitri Konidaris
2019	A*	`conf`	State Abstraction as Compression in Apprenticeship Learning. AAAI David Abel, Dilip Arumugam, Kavosh Asadi, Yuu Jinnai, Michael L. Littman, Lawson L. S. Wong
2018	J	`jnl`	Equivalence Between Wasserstein and Value-Aware Model-based Reinforcement Learning. CoRR Kavosh Asadi, Evan Cater, Dipendra Misra, Michael L. Littman
2018	A*	`conf`	Lipschitz Continuity in Model-based Reinforcement Learning. ICML Kavosh Asadi, Dipendra Misra, Michael L. Littman
2018	J	`jnl`	Lipschitz Continuity in Model-based Reinforcement Learning. CoRR Kavosh Asadi, Dipendra Misra, Michael L. Littman
2018	J	`jnl`	Mitigating Planner Overfitting in Model-Based Reinforcement Learning. CoRR Dilip Arumugam, David Abel, Kavosh Asadi, Nakul Gopalan, Christopher Grimm, Jun Ki Lee, Lucas Lehnert, Michael L. Littman
2018	J	`jnl`	Towards a Simple Approach to Multi-step Model-based Reinforcement Learning. CoRR Kavosh Asadi, Evan Cater, Dipendra Misra, Michael L. Littman
2017	A*	`conf`	An Alternative Softmax Operator for Reinforcement Learning. ICML Kavosh Asadi, Michael L. Littman
2017	—	`conf`	Hybrid Code Networks: practical and efficient end-to-end dialog control with supervised and reinforcement learning. ACL (1) Jason D. Williams, Kavosh Asadi, Geoffrey Zweig
2017	J	`jnl`	Hybrid Code Networks: practical and efficient end-to-end dialog control with supervised and reinforcement learning. CoRR Jason D. Williams, Kavosh Asadi, Geoffrey Zweig
2017	J	`jnl`	Mean Actor Critic. CoRR Kavosh Asadi, Cameron Allen, Melrose Roderick, Abdel-rahman Mohamed, George Dimitri Konidaris, Michael L. Littman
2016	J	`jnl`	A New Softmax Operator for Reinforcement Learning. CoRR Kavosh Asadi, Michael L. Littman
2016	J	`jnl`	Sample-efficient Deep Reinforcement Learning for Dialog Control. CoRR Kavosh Asadi, Jason D. Williams