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ORCIDAmir-massoud Farahmand
Person information
- affiliation: Vector Institute, Toronto, ON, Canada
- affiliation: University of Toronto, ON, Canada
- affiliation (former): Mitsubishi Electric Research Laboratories (MERL)
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Journal Articles
- 2016
[j5]Amir-massoud Farahmand, Mohammad Ghavamzadeh, Csaba Szepesvári, Shie Mannor:
Regularized Policy Iteration with Nonparametric Function Spaces. J. Mach. Learn. Res. 17: 139:1-139:66 (2016)- 2015
- [j4]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): 87-98 (2015) - [j3]Amir-massoud Farahmand, Doina Precup, André da Motta Salles Barreto, Mohammad Ghavamzadeh:
Classification-Based Approximate Policy Iteration. IEEE Trans. Autom. Control. 60(11): 2989-2993 (2015) - 2011
- [j2]Amir Massoud Farahmand, Csaba Szepesvári:
Model selection in reinforcement learning. Mach. Learn. 85(3): 299-332 (2011) - 2010
- [j1]Amir Massoud Farahmand, Majid Nili Ahmadabadi, Caro Lucas, Babak Nadjar Araabi:
Interaction of Culture-Based Learning and Cooperative Co-Evolution and its Application to Automatic Behavior-Based System Design. IEEE Trans. Evol. Comput. 14(1): 23-57 (2010)
Conference and Workshop Papers
- 2023
- [c41]Tyler Kastner, Murat A. Erdogdu, Amir-massoud Farahmand:
Distributional Model Equivalence for Risk-Sensitive Reinforcement Learning. NeurIPS 2023 - 2022
- [c40]Guiliang Liu, Ashutosh Adhikari, Amir-massoud Farahmand, Pascal Poupart:
Learning Object-Oriented Dynamics for Planning from Text. ICLR 2022 - [c39]Claas Voelcker, Victor Liao, Animesh Garg, Amir-massoud Farahmand:
Value Gradient weighted Model-Based Reinforcement Learning. ICLR 2022 - [c38]Amin Rakhsha, Andrew Wang, Mohammad Ghavamzadeh, Amir-massoud Farahmand:
Operator Splitting Value Iteration. NeurIPS 2022 - [c37]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: 1561-1571 - 2021
- [c36]Amir Massoud Farahmand, Mohammad Ghavamzadeh:
PID Accelerated Value Iteration Algorithm. ICML 2021: 3143-3153 - 2020
- [c35]Yangchen Pan, Jincheng Mei, Amir-massoud Farahmand:
Frequency-based Search-control in Dyna. ICLR 2020 - [c34]Yangchen Pan, Ehsan Imani, Amir-massoud Farahmand, Martha White:
An implicit function learning approach for parametric modal regression. NeurIPS 2020 - 2019
- [c33]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 - [c32]Yangchen Pan, Hengshuai Yao, Amir-massoud Farahmand, Martha White:
Hill Climbing on Value Estimates for Search-control in Dyna. IJCAI 2019: 3209-3215 - [c31]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: 549-557 - [c30]Amir-massoud Farahmand:
Value Function in Frequency Domain and the Characteristic Value Iteration Algorithm. NeurIPS 2019: 14780-14790 - 2018
- [c29]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: 3983-3992 - [c28]Amir-massoud Farahmand:
Iterative Value-Aware Model Learning. NeurIPS 2018: 9090-9101 - 2017
- [c27]Amir Massoud Farahmand, André Barreto, Daniel Nikovski:
Value-Aware Loss Function for Model-based Reinforcement Learning. AISTATS 2017: 1486-1494 - [c26]Amir-massoud Farahmand, Saleh Nabi, Daniel Nikolaev Nikovski:
Deep reinforcement learning for partial differential equation control. ACC 2017: 3120-3127 - [c25]Amir-massoud Farahmand, Sepideh Pourazarm, Daniel Nikovski:
Random Projection Filter Bank for Time Series Data. NIPS 2017: 6562-6572 - [c24]Devesh K. Jha, Daniel Nikovski, William Yerazunis, Amir-massoud Farahmand:
Learning to regulate rolling ball motion. SSCI 2017: 1-6 - 2016
- [c23]Amir-massoud Farahmand, Daniel Nikolaev Nikovski, Yuji Igarashi, Hiroki Konaka:
Truncated Approximate Dynamic Programming with Task-Dependent Terminal Value. AAAI 2016: 3123-3129 - [c22]Mouhacine Benosman, Amir-massoud Farahmand, Meng Xia:
Learning-based modular indirect adaptive control for a class of nonlinear systems. ACC 2016: 733-738 - [c21]Amir-massoud Farahmand, Saleh Nabi, Piyush Grover, Daniel Nikovski:
Learning to control partial differential equations: Regularized Fitted Q-Iteration approach. CDC 2016: 4578-4585 - 2015
- [c20]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: 2673-2679 - 2014
- [c19]Philip Bachman, Amir-massoud Farahmand, Doina Precup:
Sample-based approximate regularization. ICML 2014: 1926-1934 - 2013
- [c18]Beomjoon Kim, Amir-massoud Farahmand, Joelle Pineau, Doina Precup:
Learning from Limited Demonstrations. NIPS 2013: 2859-2867 - [c17]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: 3030-3038 - 2012
- [c16]Amir Massoud Farahmand, Doina Precup:
Value Pursuit Iteration. NIPS 2012: 1349-1357 - 2011
- [c15]Amir Massoud Farahmand:
Action-Gap Phenomenon in Reinforcement Learning. NIPS 2011: 172-180 - 2010
- [c14]Azad Shademan, Amir Massoud Farahmand, Martin Jägersand:
Robust Jacobian estimation for uncalibrated visual servoing. ICRA 2010: 5564-5569 - [c13]Amir Massoud Farahmand, Rémi Munos, Csaba Szepesvári:
Error Propagation for Approximate Policy and Value Iteration. NIPS 2010: 568-576 - 2009
- [c12]Amir Massoud Farahmand, Mohammad Ghavamzadeh, Csaba Szepesvári, Shie Mannor:
Regularized Fitted Q-Iteration for planning in continuous-space Markovian decision problems. ACC 2009: 725-730 - [c11]Azad Shademan, Amir Massoud Farahmand, Martin Jägersand:
Towards Learning Robotic Reaching and Pointing: An Uncalibrated Visual Servoing Approach. CRV 2009: 229-236 - [c10]Amir Massoud Farahmand, Azad Shademan, Martin Jägersand, Csaba Szepesvári:
Model-based and model-free reinforcement learning for visual servoing. ICRA 2009: 2917-2924 - 2008
- [c9]Amir Massoud Farahmand, Mohammad Ghavamzadeh, Csaba Szepesvári, Shie Mannor:
Regularized Fitted Q-Iteration: Application to Planning. EWRL 2008: 55-68 - [c8]Amir Massoud Farahmand, Mohammad Ghavamzadeh, Csaba Szepesvári, Shie Mannor:
Regularized Policy Iteration. NIPS 2008: 441-448 - 2007
- [c7]Amir Massoud Farahmand, Csaba Szepesvári, Jean-Yves Audibert:
Manifold-adaptive dimension estimation. ICML 2007: 265-272 - [c6]Amir Massoud Farahmand, Azad Shademan, Martin Jägersand:
Global visual-motor estimation for uncalibrated visual servoing. IROS 2007: 1969-1974 - 2006
- [c5]Amir Massoud Farahmand, Majid Nili Ahmadabadi, Caro Lucas, Babak Nadjar Araabi:
Hybrid Behavior Co-evolution and Structure Learning in Behavior-based Systems. IEEE Congress on Evolutionary Computation 2006: 275-282 - [c4]Mohammad G. Azar, Majid Nili Ahmadabadi, Amir Massoud Farahmand, Babak Nadjar Araabi:
Learning to Coordinate Behaviors in Soft Behavior-Based Systems Using Reinforcement Learning. IJCNN 2006: 241-248 - [c3]Amir Massoud Farahmand, Mohammad Javad Yazdanpanah:
Channel Assignment using Chaotic Simulated Annealing Enhanced Hopfield Neural Network. IJCNN 2006: 4491-4497 - 2005
- [c2]Amir Massoud Farahmand, Mohammad Javad Yazdanpanah:
Locally Optimal Takagi-Sugeno Fuzzy Controllers. CDC/ECC 2005: 4095-4099 - 2004
- [c1]Amir Massoud Farahmand, Majid Nili Ahmadabadi, Babak Nadjar Araabi:
Behavior hierarchy learning in a behavior-based system using reinforcement learning. IROS 2004: 2050-2055
Informal and Other Publications
- 2024
- [i24]Marcel Hussing, Claas Voelcker, Igor Gilitschenski, Amir-massoud Farahmand, Eric Eaton:
Dissecting Deep RL with High Update Ratios: Combatting Value Overestimation and Divergence. CoRR abs/2403.05996 (2024) - 2023
- [i23]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 abs/2306.17366 (2023) - [i22]Tyler Kastner, Murat A. Erdogdu, Amir-massoud Farahmand:
Distributional Model Equivalence for Risk-Sensitive Reinforcement Learning. CoRR abs/2307.01708 (2023) - [i21]Mete Kemertas, Allan D. Jepson, Amir-massoud Farahmand:
Efficient and Accurate Optimal Transport with Mirror Descent and Conjugate Gradients. CoRR abs/2307.08507 (2023) - [i20]Avery Ma, Yangchen Pan, Amir-massoud Farahmand:
Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods. CoRR abs/2308.06703 (2023) - [i19]Amin Rakhsha, Mete Kemertas, Mohammad Ghavamzadeh, Amir-massoud Farahmand:
Maximum Entropy Model Correction in Reinforcement Learning. CoRR abs/2311.17855 (2023) - [i18]Avery Ma, Amir-massoud Farahmand, Yangchen Pan, Philip H. S. Torr, Jindong Gu:
Improving Adversarial Transferability via Model Alignment. CoRR abs/2311.18495 (2023) - 2022
- [i17]Claas Voelcker, Victor Liao, Animesh Garg, Amir-massoud Farahmand:
Value Gradient weighted Model-Based Reinforcement Learning. CoRR abs/2204.01464 (2022) - [i16]Amin Rakhsha, Andrew Wang, Mohammad Ghavamzadeh, Amir-massoud Farahmand:
Operator Splitting Value Iteration. CoRR abs/2211.13937 (2022) - 2021
- [i15]Erfan Pirmorad, Faraz Khoshbakhtian, Farnam Mansouri, Amir-massoud Farahmand:
Deep Reinforcement Learning for Online Control of Stochastic Partial Differential Equations. CoRR abs/2110.11265 (2021) - 2020
- [i14]Yangchen Pan, Jincheng Mei, Amir-massoud Farahmand:
Frequency-based Search-control in Dyna. CoRR abs/2002.05822 (2020) - [i13]Yangchen Pan, Ehsan Imani, Martha White, Amir-massoud Farahmand:
An implicit function learning approach for parametric modal regression. CoRR abs/2002.06195 (2020) - [i12]Romina Abachi, Mohammad Ghavamzadeh, Amir-massoud Farahmand:
Policy-Aware Model Learning for Policy Gradient Methods. CoRR abs/2003.00030 (2020) - [i11]Avery Ma, Fartash Faghri, Amir-massoud Farahmand:
Adversarial Robustness through Regularization: A Second-Order Approach. CoRR abs/2004.01832 (2020) - [i10]Jincheng Mei, Yangchen Pan, Martha White, Amir-massoud Farahmand, Hengshuai Yao:
Beyond Prioritized Replay: Sampling States in Model-Based RL via Simulated Priorities. CoRR abs/2007.09569 (2020) - [i9]Rodrigo Toro Icarte, Richard Anthony Valenzano, Toryn Q. Klassen, Phillip J. K. Christoffersen, Amir-massoud Farahmand, Sheila A. McIlraith:
The act of remembering: a study in partially observable reinforcement learning. CoRR abs/2010.01753 (2020) - 2019
- [i8]Mohamed Akrout, Amir-massoud Farahmand, Tory Jarmain, Latif Abid:
Improving Skin Condition Classification with a Visual Symptom Checker Trained using Reinforcement Learning. CoRR abs/1903.03495 (2019) - [i7]Yangchen Pan, Hengshuai Yao, Amir-massoud Farahmand, Martha White:
Hill Climbing on Value Estimates for Search-control in Dyna. CoRR abs/1906.07791 (2019) - 2018
- [i6]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 abs/1806.06931 (2018) - [i5]Mohamed Akrout, Amir-massoud Farahmand, Tory Jarmain:
Improving Skin Condition Classification with a Question Answering Model. CoRR abs/1811.06165 (2018) - 2017
- [i4]Kota Hara, Ming-Yu Liu, Oncel Tuzel, Amir-massoud Farahmand:
Attentional Network for Visual Object Detection. CoRR abs/1702.01478 (2017) - 2015
- [i3]Mouhacine Benosman, Amir-massoud Farahmand, Meng Xia:
Learning-Based Modular Indirect Adaptive Control for a Class of Nonlinear Systems. CoRR abs/1509.07860 (2015) - 2014
- [i2]Amir-massoud Farahmand, Doina Precup, André da Motta Salles Barreto, Mohammad Ghavamzadeh:
Classification-based Approximate Policy Iteration: Experiments and Extended Discussions. CoRR abs/1407.0449 (2014) - 2012
- [i1]Mahdi Milani Fard, Yuri Grinberg, Amir Massoud Farahmand, Joelle Pineau, Doina Precup:
Bellman Error Based Feature Generation using Random Projections on Sparse Spaces. CoRR abs/1207.5554 (2012)
Coauthor Index
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