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Amir-Massoud FarahmandDepartment of Computer Engineering and Software Engineering
Profile in the Directory of Experts of Polytechnique Montréal
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Abachi, R., Voelcker, C. A., Garg, A., & Farahmand, A.-M. (2022, July). VIPer : iterative value-aware model learning on the value improvement path [Paper]. Decision Awareness in Reinforcement Learning Workshop (DARL 2022), Baltimore, MD, USA (10 pages). External link
Akrout, M., Farahmand, A.-M., Jarmain, T., & Abid, L. (2019, October). Improving Skin Condition Classification with a Visual Symptom Checker Trained Using Reinforcement Learning [Paper]. 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2019), Shenzhen, China. External link
Azar, M. G., Ahmadabadi, M. N., Farahmand, A.-M., & Araabi, B. N. (2006, July). Learning to Coordinate Behaviors in Soft Behavior-Based Systems Using Reinforcement Learning [Paper]. IEEE International Joint Conference on Neural Network Proceedings (IJCNN 2006), Vancouver, BC, Canada. External link
Bedaywi, M., Rakhsha, A., & Farahmand, A.-M. (2024, August). PID accelerated temporal difference algorithms [Paper]. Reinforcement Learning Conference (RLC 2024), Amherst, Massachusetts, USA (25 pages). External link
Bedaywi, M., & Farahmand, A.-M. (2021, July). PID accelerated temporal difference algorithms [Paper]. 38th International Conference on Machine Learning (ICML 2021), En ligne / Online. External link
Benosman, M., Farahmand, A.-M., & Xia, M. (2019). Learning-based iterative modular adaptive control for nonlinear systems. International Journal of Adaptive Control and Signal Processing, 33(2), 335-355. External link
Benosman, M., Farahmand, A.-M., & Xia, M. (2016, July). Learning-based modular indirect adaptive control for a class of nonlinear systems [Paper]. American Control Conference (ACC 2016), Boston, MA, USA. External link
Bagnell, J. A., & Farahmand, A.-M. (2015, December). Learning positive functions in a Hilbert Space [Paper]. 8th NIPS Workshop on Optimization for Machine Learning (OPT 2015), Montreal, Qc, Canada (10 pages). External link
Bachman, P., Farahmand, A.-M., & Precup, D. (2014, June). Sample-based approximate regularization [Paper]. 31st International Conference on Machine Learning (ICML 2014), Beijing, China (9 pages). External link
Farahmand, A.-M. (2019, December). Value function in frequency domain and the characteristic value iteration algorithm [Paper]. 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, BC, Canada (12 pages). External link
Farahmand, A.-M. (2018, December). Iterative value-aware model learning [Paper]. 32th Conference on Neural Information Processing Systems (NeurIPS 2018), Montreal, Qc, Canada (12 pages). External link
Farahmand, A.-M., Nabi, S., & Nikovski, D. N. (2017, May). Deep reinforcement learning for partial differential equation control [Paper]. American Control Conference (ACC 2017), Seattle, WA, USA. External link
Farahmand, A.-M., Pourazarm, S., & Nikovski, D. N. (2017, December). Random projection filter bank for time series data [Paper]. 31st annual Conference on Neural Information Processing systsems (NeurIPS 2017), Long Beauch, CA, USA (11 pages). External link
Farahmand, A.-M., Barreto, A. M., & Nikovski, D. N. (2017, April). Value-aware loss function for model-based reinforcement learning [Paper]. 20th International Conference on Artificial Intelligence and Statistics (AISTATS 2017), Fort Lauderdale, FL, USA. External link
Farahmand, A.-M., Nabi, S., Grover, P., & Nikovski, D. N. (2016, December). Learning to control partial differential equations: Regularized Fitted Q-Iteration approach [Paper]. 55th IEEE Conference on Decision and Control (CDC 2016), Las Vegas, NV, USA (8 pages). External link
Farahmand, A.-M., Ghavamzadeh, M., Szepesvari, C., & Mannor, S. (2016). Regularized policy iteration with non parametric function spaces. Journal of Machine Learning Research, 17(139), 66 pages. External link
Farahmand, A.-M., Nikovski, D. N., Igarashi, Y., & Konaka, H. (2016, February). Truncated approximate dynamic programming with task-dependent terminal value [Abstract]. 30th AAAI Conference on Artificial Intelligence (AAAI 2016), Phoenix, Arizona, USA. External link
Farahmand, A.-M. (2016, December). Value-aware loss function for model-based reinforcement learning [Paper]. 13th European Workshop on Reinforcement Learning (EWRL 2016), Barcelona, Spain (8 pages). External link
Farahmand, A.-M., Precup, D., Barreto, A. M., & Ghavamzadeh, M. (2015). Classification-Based Approximate Policy Iteration. IEEE Transactions on Automatic Control, 60(11), 2989-2993. External link
Fard, M. M., Grinberg, Y., Farahmand, A.-M., Pineau, J., & Precup, D. (2013, December). Bellman error based feature generation using random projections on sparse spaces [Paper]. 27th Conference on Neural Information Processing Systems (NeurIPS 2013), Las Vegas, NV, USA (9 pages). External link
Farahmand, A.-M., Precup, D., Barreto, A. M. S., & Ghavamzadeh, M. (2013, October). CAPI : generalized classification-based approximate policy iteration [Paper]. Multi-Disciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2013), Princeton, NJ, USA. Unavailable
Farahmand, A.-M. (2016, December). Iterative value-aware model learning [Presentation]. In 13th European Workshop on Reinforcement Learning (EWRL 2016), Barcelona, Spain. Unavailable
Farahmand, A.-M., & Szepesvári, C. (2012). Regularized least-squares regression: Learning from a β-mixing sequence. Journal of Statistical Planning and Inference, 142(2), 493-505. External link
Farahmand, A.-M., & Precup, D. (2012, December). Value pursuit iteration [Paper]. 26th annual Conference on Neural Information Processing Systems (NeurIPS 2012), Lake Tahoe, Nevada, USA (9 pages). External link
Farahmand, A.-M. (2011, December). Action-Gap phenomenon in reinforcement learning [Paper]. 25th annual Conference on Neural Information Processing Systems (NeurIPS 2011), Granada, Spain (9 pages). External link
Farahmand, A.-M., & Szepesvári, C. (2011). Model selection in reinforcement learning. Machine Learning, 85(3), 299-332. External link
Farahmand, A.-M. (2011). Regularization in reinforcement learning [Ph.D. Thesis, University of Alberta]. External link
Farahmand, A.-M., Szepesvari, C., & Munos, R. (2010, December). Error propagation for approximate policy and value iteration [Paper]. 24th annual Conference on Neural Information Processing Systems (NeurIPS 2010), Vancouver, CB, Canada (9 pages). External link
Farahmand, A.-M., Ahmadabadi, M. N., Lucas, C., & Araabi, B. N. (2010). Interaction of Culture-Based Learning and Cooperative Co-Evolution and its Application to Automatic Behavior-Based System Design. IEEE Transactions on Evolutionary Computation, 14(1), 23-57. External link
Farahmand, A.-M., Shademan, A., Jägersand, M., & Szepesvári, C. (2009, May). Model-based and model-free reinforcement learning for visual servoing [Paper]. IEEE International Conference on Robotics and Automation, Kobe, Japan. External link
Farahmand, A.-M., Ghavamzadeh, M., Szepesvári, C., & Mannor, S. (2009, June). Regularized Fitted Q-Iteration for planning in continuous-space Markovian decision problems [Paper]. American Control Conference (ACC 2009), St. Louis, MO, USA. External link
Farahmand, A.-M., Ghavamzadeh, M., Szepesvári, C., & Mannor, S. (2008, June). Regularized Fitted Q-Iteration: Application to Planning [Paper]. 8th European Workshop on Recent Advances in Reinforcement Learning (EWRL 2008), Villeneuve d'Ascq, France. External link
Farahmand, A.-M., Ghavamzadeh, M., Szepesvari, C., & Mannor, S. (2008, December). Regularized policy iteration [Paper]. 22th annual Conference on Neural Information Processing Systems (NeurIPS 2008), Vancouver, CB, Canada (8 pages). External link
Farahmand, A.-M., Shademan, A., & Jägersand, M. (2007, October). Global visual-motor estimation for uncalibrated visual servoing [Paper]. IEEE/RSJ International Conference on Intelligent Robots and Systems, San Diego, CA, USA. External link
Farahmand, A.-M., Szepesvári, C., & Audibert, J.-Y. (2007, June). Manifold-adaptive dimension estimation [Paper]. 24th international conference on Machine learning (ICML 2007), Corvalis, Oregon, USA. External link
Farahmand, A.-M., & Yazdanpanah, M. J. (2006, July). Channel Assignment using Chaotic Simulated Annealing Enhanced Hopfield Neural Network [Paper]. IEEE International Joint Conference on Neural Network Proceedings (IJCNN 2006), Vancouver, BC, Canada. External link
Farahmand, A.-M. (2005). Learning and evolution in hierarchical behavior-based systems [Master's Thesis, University of Tehran]. Unavailable
Farahmand, A.-M. (2002). Calculating resonant frequencies of a metallic cavity using finite element method [Master's Thesis, K.N. Toosi University of Technology]. Unavailable
Farahmand, A.-M., Akhbari, R., & Tajvidi, M. (2001, March). Evolving hidden Markov models [Paper]. 4th Iranian Student Conference on Electrical Engineering (ISCEE 2001), Tehran, Iran. Unavailable
Farahmand, A.-M., & Mirmirani, E. (2000, January). Distributed genetic algorithms [Paper]. 3rd Iranian Student Conference on Electrical Engineering (ISCEE 2000), Tehran, Iran. Unavailable
Hussing, M., Voelcker, C. A., Gilitschenski, I., Farahmand, A.-M., & Eaton, E. (2024, August). Dissecting Deep RL with high update ratios : combatting value divergence [Paper]. Reinforcement Learning Conference (RLC 2024), Amherst, Massachusetts, USA (24 pages). External link
Huang, D.-A., Farahmand, A.-M., Kitani, K. M., & Bagnell, J. A. (2015, June). Approximate MaxEnt inverse optimal control [Paper]. Reinforcement Learning and Decision Making (RLDM 2015), Edmonton, AB, CAnada (5 pages). External link
Huang, D.-A., Farahmand, A.-M., Kitani, K. M., & Bagnell, J. A. (2015, January). Approximate maxent inverse optimal control and its application for mental simulation of human interactions [Abstract]. 29th AAAI Conference on Artificial Intelligence (AAAI 2015), Austin, Texas, USA. External link
Kemertas, M., Farahmand, A.-M., & Jepson, A. D. (2025, April). A truncated newton method for optimal transport [Paper]. 13th International Conference on Learning Representations (ICLR 2025), Singapore, Singapore. External link
Kastner, T., Erdogdu, M. A., & Farahmand, A.-M. (2023, December). Distributional model equivalence for risk-sensitive reinforcement learning [Paper]. 37th Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, Louisiana, USA (22 pages). External link
Kim, B., Farahmand, A.-M., Pineau, J., & Precup, D. (2013, October). Approximate policy iteration with demonstrated data [Paper]. Multi-Disciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2013), Princeton, NJ, USA. Unavailable
Kim, B., Farahmand, A.-M., Pineau, J., & Precup, D. (2013, December). Learning from limited demonstration [Paper]. 27th Conference on Neural Information Processing Systems (NeurIPS 2013), Las Vegas, NV, USA (9 pages). External link
Liu, G., Adhikari, A. S., Farahmand, A.-M., & Poupart, P. (2022, April). Learning object-oriented dynamics for planning form text [Poster]. 10th International Conference on Learning Representations (ICLR 2022), En ligne / Online. External link
Law, M. T., Snell, J., Farahmand, A.-M., Urtasun, R., & Zemel, R. S. (2019, May). Dimensionality reduction for representing the knowledge of prababilistic models [Paper]. 7th International Conference on Learning Representations (ICLR 2019), New Orleans, Louisiana (34 pages). External link
Ma, A., Farahmand, A.-M., Pan, Y., Torr, P., & Gu, J. (2024, September). Improving Adversarial Transferability via Model Alignment [Paper]. 18th European Conference on Computer Vision (ECCV 2024), Milan, Italy. External link
Ma, A., Pan, Y., & Farahmand, A.-M. (2023). Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods. Transactions on Machine Learning Research, 57 pages. External link
Nikovski, D. N., Zhu, Y., & Farahmand, A.-M. (2020). Methods and systems for discovery of prognostic subsequences in time series. (Patent no. US10712733). External link
Pirmorad, E., Mansouri, F., & Farahmand, A.-M. (2024, December). Deep reinforcement learning for online control of stochastic partial differenctial equations [Paper]. 38th Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, BC, Canada (6 pages). External link
Pan, Y., Mei, J., Farahmand, A.-M., White, M., Yao, H., Rohani, M., & Luo, J. (2022, August). Understanding and mitigating the limitations of prioritized experience replay [Paper]. 38th Conference on Uncertainty in Artificial Intelligence (UIA 2022), Eindhoven, The Netherlands. External link
Pan, Y., Mei, J., & Farahmand, A.-M. (2020, April). Frequency-based search-control in Dyna [Paper]. 8th International Conference on Learning Representations (ICLR 2020), En ligne / Online (21 pages). External link
Pan, Y., Imani, E., Farahmand, A.-M., & White, M. (2020, December). An implicit function learning approach for parametric modal regression [Paper]. 34th Conference on Neural Information Processing Systems (NeurIPS 2020), En ligne / Online (11 pages). External link
Pan, Y., Yao, H., Farahmand, A.-M., & White, M. (2019, August). Hill climbing on value estimates for search-control in Dyna [Paper]. 28th International Joint Conference on Artificial Intelligence (IJCAI-19), Macao, China. Unavailable
Pan, Y., Farahmand, A.-M., White, M., Nabi, S., Gover, P., & Nikovski, D. (2018, July). Reinforcement learning with function-valued action spaces for partial differential equation control [Paper]. 35th International Conference on Machine Learning (ICML 2018), Stockholm, Sweden. External link
Pourazarm, S., Farahmand, A.-M., & Nikovski, D. N. (2017, October). Fault detection and prognosis of time series data with random projection filter bank [Paper]. 9th annual Conference of the Prognostics and Health Management Society (PHM 2017), St. Petersburg, FL, USA (11 pages). External link
Rakhsha, A., Kemertas, M., Ghavamzadeh, M., & Farahmand, A.-M. (2024, May). Maximum entropy model correction in reinforcement learning [Presentation]. In 12th International Conference on Learning Representations (ICLR 2024), Vienna, Austria. External link
Rakhsha, A., Wang, A., Ghavamzadeh, M., & Farahmand, A.-M. (2022, December). Operator splitting value iteration [Presentation]. In 37th annual Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, Louisiana, USA (13 pages). External link
Shademan, A., Farahmand, A.-M., & Jägersand, M. (2010, May). Robust Jacobian estimation for uncalibrated visual servoing [Paper]. IEEE International Conference on Robotics and Automation (ICRA 2010), Anchorage, AK, USA. External link
Shademan, A., Farahmand, A.-M., & Jägersand, M. (2009, May). Towards Learning Robotic Reaching and Pointing: An Uncalibrated Visual Servoing Approach [Paper]. Canadian Conference on Computer and Robot Vision (CCRV 2009), Kelowna, BC, Canada. External link
Voelcker, C. A., Kastner, T., Gilitschenski, I., & Farahmand, A.-M. (2024, August). When does self-prediction help? Understanding auxiliary tasks in reinforcement learning [Paper]. Reinforcement Learning Conference (RLC 2024), Amherst, Massachusetts, USA (31 pages). External link
Voelcker, C. A., Liao, V., Garg, A., & Farahmand, A.-M. (2022, April). Value gradient weighted model-based reinforcement learning [Poster]. 10th International Conference on Learning Representations (ICLR 2022), En ligne / Online. External link
