Amir-massoud Farahmand

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 50

Top Topics

Reinforcement Learning

Approximate Dynamic Programming

Top Venues

Publications

Amin Rakhsha, Mete Kemertas, Mohammad Ghavamzadeh, Amir-massoud Farahmand
Maximum Entropy Model Correction in Reinforcement Learning. ICLR (2024)
Mark Bedaywi, Amin Rakhsha, Amir-massoud Farahmand
PID Accelerated Temporal Difference Algorithms. CoRR (2024)
Claas Voelcker, Tyler Kastner, Igor Gilitschenski, Amir-massoud Farahmand
When does Self-Prediction help? Understanding Auxiliary Tasks in Reinforcement Learning. CoRR (2024)
Marcel Hussing, Claas Voelcker, Igor Gilitschenski, Amir-massoud Farahmand, Eric Eaton
Dissecting Deep RL with High Update Ratios: Combatting Value Overestimation and Divergence. CoRR (2024)
Jongmin Lee, Amin Rakhsha, Ernest K. Ryu, Amir-massoud Farahmand
Deflated Dynamics Value Iteration. CoRR (2024)
Avery Ma, Yangchen Pan, Amir-massoud Farahmand
Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods. CoRR (2023)
Tyler Kastner, Murat A. Erdogdu, Amir-massoud Farahmand
Distributional Model Equivalence for Risk-Sensitive Reinforcement Learning. NeurIPS (2023)
Amin Rakhsha, Mete Kemertas, Mohammad Ghavamzadeh, Amir-massoud Farahmand
Maximum Entropy Model Correction in Reinforcement Learning. CoRR (2023)
Mete Kemertas, Allan D. Jepson, Amir-massoud Farahmand
Efficient and Accurate Optimal Transport with Mirror Descent and Conjugate Gradients. CoRR (2023)
Avery Ma, Amir-massoud Farahmand, Yangchen Pan, Philip Torr, Jindong Gu
Improving Adversarial Transferability via Model Alignment. CoRR (2023)
Claas Voelcker, Arash Ahmadian, Romina Abachi, Igor Gilitschenski, Amir-massoud Farahmand
λ-AC: Learning latent decision-aware models for reinforcement learning in continuous state-spaces. CoRR (2023)
Tyler Kastner, Murat A. Erdogdu, Amir-massoud Farahmand
Distributional Model Equivalence for Risk-Sensitive Reinforcement Learning. CoRR (2023)
Avery Ma, Yangchen Pan, Amir-massoud Farahmand
Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods. Trans. Mach. Learn. Res. 2023 (2023)
Claas Voelcker, Victor Liao, Animesh Garg, Amir-massoud Farahmand
Value Gradient weighted Model-Based Reinforcement Learning. ICLR (2022)
Amin Rakhsha, Andrew Wang, Mohammad Ghavamzadeh, Amir-massoud Farahmand
Operator Splitting Value Iteration. NeurIPS (2022)
Claas Voelcker, Victor Liao, Animesh Garg, Amir-massoud Farahmand
Value Gradient weighted Model-Based Reinforcement Learning. CoRR (2022)
Yangchen Pan, Jincheng Mei, Amir-massoud Farahmand, Martha White, Hengshuai Yao, Mohsen Rohani, Jun Luo
Understanding and mitigating the limitations of prioritized experience replay. UAI (2022)
Amin Rakhsha, Andrew Wang, Mohammad Ghavamzadeh, Amir-massoud Farahmand
Operator Splitting Value Iteration. CoRR (2022)
Guiliang Liu, Ashutosh Adhikari, Amir-massoud Farahmand, Pascal Poupart
Learning Object-Oriented Dynamics for Planning from Text. ICLR (2022)
Erfan Pirmorad, Faraz Khoshbakhtian, Farnam Mansouri, Amir-massoud Farahmand
Deep Reinforcement Learning for Online Control of Stochastic Partial Differential Equations. CoRR (2021)
Avery Ma, Fartash Faghri, Amir-massoud Farahmand
Adversarial Robustness through Regularization: A Second-Order Approach. CoRR (2020)
Jincheng Mei, Yangchen Pan, Martha White, Amir-massoud Farahmand, Hengshuai Yao
Beyond Prioritized Replay: Sampling States in Model-Based RL via Simulated Priorities. CoRR (2020)
Romina Abachi, Mohammad Ghavamzadeh, Amir-massoud Farahmand
Policy-Aware Model Learning for Policy Gradient Methods. CoRR (2020)
Rodrigo Toro Icarte, Richard Anthony Valenzano, Toryn Q. Klassen, Phillip Christoffersen, Amir-massoud Farahmand, Sheila A. McIlraith
The act of remembering: a study in partially observable reinforcement learning. CoRR (2020)
Yangchen Pan, Ehsan Imani, Martha White, Amir-massoud Farahmand
An implicit function learning approach for parametric modal regression. CoRR (2020)
Yangchen Pan, Jincheng Mei, Amir-massoud Farahmand
Frequency-based Search-control in Dyna. ICLR (2020)
Yangchen Pan, Jincheng Mei, Amir-massoud Farahmand
Frequency-based Search-control in Dyna. CoRR (2020)
Yangchen Pan, Ehsan Imani, Amir-massoud Farahmand, Martha White
An implicit function learning approach for parametric modal regression. NeurIPS (2020)
Yangchen Pan, Hengshuai Yao, Amir-massoud Farahmand, Martha White
Hill Climbing on Value Estimates for Search-control in Dyna. IJCAI (2019)
Marc T. Law, Jake Snell, Amir-massoud Farahmand, Raquel Urtasun, Richard S. Zemel
Dimensionality Reduction for Representing the Knowledge of Probabilistic Models. ICLR (Poster) (2019)
Amir-massoud Farahmand
Value Function in Frequency Domain and the Characteristic Value Iteration Algorithm. NeurIPS (2019)
Mohamed Akrout, Amir-massoud Farahmand, Tory Jarmain, Latif Abid
Improving Skin Condition Classification with a Visual Symptom Checker Trained using Reinforcement Learning. CoRR (2019)
Yangchen Pan, Hengshuai Yao, Amir-massoud Farahmand, Martha White
Hill Climbing on Value Estimates for Search-control in Dyna. CoRR (2019)
Mohamed Akrout, Amir-massoud Farahmand, Tory Jarmain, Latif Abid
Improving Skin Condition Classification with a Visual Symptom Checker Trained Using Reinforcement Learning. MICCAI (4) (2019)
Amir-massoud Farahmand
Iterative Value-Aware Model Learning. NeurIPS (2018)
Yangchen Pan, Amir-massoud Farahmand, Martha White, Saleh Nabi, Piyush Grover, Daniel Nikovski
Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control. ICML (2018)
Mohamed Akrout, Amir-massoud Farahmand, Tory Jarmain
Improving Skin Condition Classification with a Question Answering Model. CoRR (2018)
Yangchen Pan, Amir-massoud Farahmand, Martha White, Saleh Nabi, Piyush Grover, Daniel Nikovski
Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control. CoRR (2018)
Kota Hara, Ming-Yu Liu, Oncel Tuzel, Amir-massoud Farahmand
Attentional Network for Visual Object Detection. CoRR (2017)
Amir-massoud Farahmand, Sepideh Pourazarm, Daniel Nikovski
Random Projection Filter Bank for Time Series Data. NIPS (2017)
Amir-massoud Farahmand, Saleh Nabi, Daniel Nikolaev Nikovski
Deep reinforcement learning for partial differential equation control. ACC (2017)
Devesh K. Jha, Daniel Nikovski, William Yerazunis, Amir-massoud Farahmand
Learning to regulate rolling ball motion. SSCI (2017)
Amir-massoud Farahmand, Daniel Nikolaev Nikovski, Yuji Igarashi, Hiroki Konaka
Truncated Approximate Dynamic Programming with Task-Dependent Terminal Value. AAAI (2016)
Amir-massoud Farahmand, Saleh Nabi, Piyush Grover, Daniel Nikovski
Learning to control partial differential equations: Regularized Fitted Q-Iteration approach. CDC (2016)
Mouhacine Benosman, Amir-massoud Farahmand, Meng Xia
Learning-based modular indirect adaptive control for a class of nonlinear systems. ACC (2016)
Amir-massoud Farahmand, Mohammad Ghavamzadeh, Csaba Szepesvári, Shie Mannor
Regularized Policy Iteration with Nonparametric Function Spaces. J. Mach. Learn. Res. 17 (2016)
Stefano V. Albrecht, André da Motta Salles Barreto, Darius Braziunas, David L. Buckeridge, Heriberto Cuayáhuitl, Nina Dethlefs, Markus Endres, Amir-massoud Farahmand, Mark Fox, Lutz Frommberger, Sam Ganzfried, Yolanda Gil, Sébastien Guillet, Lawrence E. Hunter, Arnav Jhala, Kristian Kersting, George Dimitri Konidaris, Freddy Lécué, Sheila A. McIlraith, Sriraam Natarajan, Zeinab Noorian, David Poole, Rémi Ronfard, Alessandro Saffiotti, Arash Shaban-Nejad, Biplav Srivastava, Gerald Tesauro, Rosario Uceda-Sosa, Guy Van den Broeck, Martijn van Otterlo, Byron C. Wallace, Paul Weng, Jenna Wiens, Jie Zhang
Reports of the AAAI 2014 Conference Workshops. AI Mag. 36 (1) (2015)
De-An Huang, Amir-massoud Farahmand, Kris M. Kitani, James Andrew Bagnell
Approximate MaxEnt Inverse Optimal Control and Its Application for Mental Simulation of Human Interactions. AAAI (2015)
Amir-massoud Farahmand, Doina Precup, André da Motta Salles Barreto, Mohammad Ghavamzadeh
Classification-Based Approximate Policy Iteration. IEEE Trans. Autom. Control. 60 (11) (2015)
Mouhacine Benosman, Amir-massoud Farahmand, Meng Xia
Learning-Based Modular Indirect Adaptive Control for a Class of Nonlinear Systems. CoRR (2015)
Amir-massoud Farahmand, Doina Precup, André da Motta Salles Barreto, Mohammad Ghavamzadeh
Classification-based Approximate Policy Iteration: Experiments and Extended Discussions. CoRR (2014)
Philip Bachman, Amir-massoud Farahmand, Doina Precup
Sample-based approximate regularization. ICML (2014)
Beomjoon Kim, Amir-massoud Farahmand, Joelle Pineau, Doina Precup
Learning from Limited Demonstrations. NIPS (2013)
Mahdi Milani Fard, Yuri Grinberg, Amir-massoud Farahmand, Joelle Pineau, Doina Precup
Bellman Error Based Feature Generation using Random Projections on Sparse Spaces. NIPS (2013)