Mehdi Fatemi
Mehdi Fatemi
Microsoft Research
Verified email at - Homepage
Cited by
Cited by
Cognitive Control
S Haykin, M Fatemi, P Setoodeh, Y Xue
IEEE, 2012
Hybrid reward architecture for reinforcement learning
H Van Seijen, M Fatemi, J Romoff, R Laroche, T Barnes, J Tsang
Advances in Neural Information Processing Systems 30, 2017
Policy networks with two-stage training for dialogue systems
M Fatemi, LE Asri, H Schulz, J He, K Suleman
arXiv preprint arXiv:1606.03152, 2016
Cognitive control: Theory and application
M Fatemi, S Haykin
IEEE Access 2, 698-710, 2014
Medical dead-ends and learning to identify high-risk states and treatments
M Fatemi, TW Killian, J Subramanian, M Ghassemi
Advances in Neural Information Processing Systems 34, 4856-4870, 2021
Hybrid reward architecture for reinforcement learning
HH Van Seijen, SM Fatemi Booshehri, RMH Laroche, JS Romoff
US Patent 10,977,551, 2021
An empirical study of representation learning for reinforcement learning in healthcare
TW Killian, H Zhang, J Subramanian, M Fatemi, M Ghassemi
arXiv preprint arXiv:2011.11235, 2020
Using a logarithmic mapping to enable lower discount factors in reinforcement learning
H Van Seijen, M Fatemi, A Tavakoli
Advances in Neural Information Processing Systems 32, 2019
Multi-advisor reinforcement learning
R Laroche, M Fatemi, J Romoff, H van Seijen
arXiv preprint arXiv:1704.00756, 2017
Dead-ends and secure exploration in reinforcement learning
M Fatemi, S Sharma, H Van Seijen, SE Kahou
International Conference on Machine Learning, 1873-1881, 2019
Learning to represent action values as a hypergraph on the action vertices
A Tavakoli, M Fatemi, P Kormushev
arXiv preprint arXiv:2010.14680, 2020
Separation of concerns in reinforcement learning
H van Seijen, M Fatemi, J Romoff, R Laroche
arXiv preprint arXiv:1612.05159, 2016
Semi-markov offline reinforcement learning for healthcare
M Fatemi, M Wu, J Petch, W Nelson, SJ Connolly, A Benz, A Carnicelli, ...
Conference on Health, Inference, and Learning, 119-137, 2022
Observability of stochastic complex networks under the supervision of cognitive dynamic systems
M Fatemi, P Setoodeh, S Haykin
Journal of Complex Networks 5 (3), 433-460, 2017
Cognitive control in cognitive dynamic systems: A new way of thinking inspired by the brain
S Haykin, A Amiri, M Fatemi
2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement …, 2014
Discrete event control of an unmanned aircraft
M Fatemi, J Millan, J Stevenson, T Yu, S O'Young
2008 9th International Workshop on Discrete Event Systems, 352-357, 2008
Systematic rectification of language models via dead-end analysis
M Cao, M Fatemi, JCK Cheung, S Shabanian
arXiv preprint arXiv:2302.14003, 2023
Orchestrated value mapping for reinforcement learning
M Fatemi, A Tavakoli
arXiv preprint arXiv:2203.07171, 2022
Shortest-path constrained reinforcement learning for sparse reward tasks
S Sohn, S Lee, J Choi, H van Seijen, M Fatemi, H Lee
arXiv preprint arXiv:2107.06405, 2021
Post-training on RBF neural networks
F Shabaninia, M Roopaei, M Fatemi
Nonlinear Analysis: Hybrid Systems 1 (4), 491-500, 2007
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