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ORCIDMehdi Fatemi
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2020 – today
- 2024
[j5]Mehdi Fatemi
, Sepehr Ghazinoory, Shohreh Nasri, Mahdi Pakzad:
Linear Optimization Modeling for Smart Specialization in Primary Sectors of a Developing Country. IEEE Trans. Engineering Management 71: 13890-13904 (2024)- [j4]Sepehr Ghazinoory, Jinus Roshandel, Fatemeh Parvin, Shohreh Nasri, Mehdi Fatemi:
Smart city maturity models: A multidimensional synthesized approach. WIREs Data. Mining. Knowl. Discov. 14(1) (2024) - [c16]Mehdi Fatemi, Sindhu C. M. Gowda:
A Dynamical View of the Question of Why. ICLR 2024 - [c15]Meng Cao, Mehdi Fatemi, Jackie C. K. Cheung, Samira Shabanian:
Successor Features for Efficient Multi-Subject Controlled Text Generation. ICML 2024 - [i16]Mehdi Fatemi, Sindhu C. M. Gowda:
A Dynamical View of the Question of Why. CoRR abs/2402.10240 (2024) - [i15]Allen Roush, Yusuf Shabazz, Arvind Balaji, Peter Zhang, Stefano Mezza, Markus Zhang, Sanjay Basu, Sriram Vishwanath, Mehdi Fatemi, Ravid Shwartz-Ziv:
OpenDebateEvidence: A Massive-Scale Argument Mining and Summarization Dataset. CoRR abs/2406.14657 (2024) - 2023
- [c14]Meng Cao, Mehdi Fatemi, Jackie C. K. Cheung, Samira Shabanian:
Systematic Rectification of Language Models via Dead-end Analysis. ICLR 2023 - [i14]Meng Cao, Mehdi Fatemi, Jackie Chi Kit Cheung, Samira Shabanian:
Systematic Rectification of Language Models via Dead-end Analysis. CoRR abs/2302.14003 (2023) - [i13]Meng Cao, Mehdi Fatemi, Jackie Chi Kit Cheung, Samira Shabanian:
Successor Features for Efficient Multisubject Controlled Text Generation. CoRR abs/2311.04921 (2023) - 2022
- [c13]Mehdi Fatemi, Mary Wu, Jeremy Petch, Walter Nelson, Stuart J. Connolly, Alexander Benz, Anthony Carnicelli, Marzyeh Ghassemi:
Semi-Markov Offline Reinforcement Learning for Healthcare. CHIL 2022: 119-137 - [c12]Mehdi Fatemi, Arash Tavakoli:
Orchestrated Value Mapping for Reinforcement Learning. ICLR 2022 - [i12]Mehdi Fatemi, Arash Tavakoli:
Orchestrated Value Mapping for Reinforcement Learning. CoRR abs/2203.07171 (2022) - [i11]Mehdi Fatemi, Mary Wu, Jeremy Petch, Walter Nelson, Stuart J. Connolly, Alexander Benz, Anthony Carnicelli, Marzyeh Ghassemi:
Semi-Markov Offline Reinforcement Learning for Healthcare. CoRR abs/2203.09365 (2022) - 2021
- [c11]Arash Tavakoli, Mehdi Fatemi, Petar Kormushev:
Learning to Represent Action Values as a Hypergraph on the Action Vertices. ICLR 2021 - [c10]Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm van Seijen, Mehdi Fatemi, Honglak Lee:
Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks. ICML 2021: 9780-9790 - [c9]Mehdi Fatemi, Taylor W. Killian, Jayakumar Subramanian, Marzyeh Ghassemi:
Medical Dead-ends and Learning to Identify High-Risk States and Treatments. NeurIPS 2021: 4856-4870 - [i10]Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm van Seijen, Mehdi Fatemi, Honglak Lee:
Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks. CoRR abs/2107.06405 (2021) - [i9]Mehdi Fatemi, Taylor W. Killian, Jayakumar Subramanian, Marzyeh Ghassemi:
Medical Dead-ends and Learning to Identify High-risk States and Treatments. CoRR abs/2110.04186 (2021) - 2020
- [c8]Taylor W. Killian, Haoran Zhang, Jayakumar Subramanian, Mehdi Fatemi, Marzyeh Ghassemi:
An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare. ML4H@NeurIPS 2020: 139-160 - [i8]Arash Tavakoli, Mehdi Fatemi, Petar Kormushev:
Learning to Represent Action Values as a Hypergraph on the Action Vertices. CoRR abs/2010.14680 (2020) - [i7]Taylor W. Killian, Haoran Zhang, Jayakumar Subramanian, Mehdi Fatemi, Marzyeh Ghassemi:
An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare. CoRR abs/2011.11235 (2020)
2010 – 2019
- 2019
- [c7]Mehdi Fatemi, Shikhar Sharma, Harm van Seijen, Samira Ebrahimi Kahou:
Dead-ends and Secure Exploration in Reinforcement Learning. ICML 2019: 1873-1881 - [c6]Harm van Seijen, Mehdi Fatemi, Arash Tavakoli:
Using a Logarithmic Mapping to Enable Lower Discount Factors in Reinforcement Learning. NeurIPS 2019: 14111-14121 - [i6]Harm van Seijen, Mehdi Fatemi, Arash Tavakoli:
Using a Logarithmic Mapping to Enable Lower Discount Factors in Reinforcement Learning. CoRR abs/1906.00572 (2019) - 2017
- [j3]Mehdi Fatemi, Peyman Setoodeh, Simon Haykin:
Observability of stochastic complex networks under the supervision of cognitive dynamic systems. J. Complex Networks 5(3): 433-460 (2017) - [c5]Harm van Seijen, Mehdi Fatemi, Romain Laroche, Joshua Romoff, Tavian Barnes, Jeffrey Tsang:
Hybrid Reward Architecture for Reinforcement Learning. NIPS 2017: 5392-5402 - [i5]Romain Laroche, Mehdi Fatemi, Joshua Romoff, Harm van Seijen:
Multi-Advisor Reinforcement Learning. CoRR abs/1704.00756 (2017) - [i4]Harm van Seijen, Mehdi Fatemi, Joshua Romoff, Romain Laroche, Tavian Barnes, Jeffrey Tsang:
Hybrid Reward Architecture for Reinforcement Learning. CoRR abs/1706.04208 (2017) - 2016
- [c4]Mehdi Fatemi, Layla El Asri, Hannes Schulz, Jing He, Kaheer Suleman:
Policy Networks with Two-Stage Training for Dialogue Systems. SIGDIAL Conference 2016: 101-110 - [i3]Mehdi Fatemi, Layla El Asri, Hannes Schulz, Jing He, Kaheer Suleman:
Policy Networks with Two-Stage Training for Dialogue Systems. CoRR abs/1606.03152 (2016) - [i2]Harm van Seijen, Mehdi Fatemi, Joshua Romoff, Romain Laroche:
Improving Scalability of Reinforcement Learning by Separation of Concerns. CoRR abs/1612.05159 (2016) - 2014
- [j2]Mehdi Fatemi, Simon Haykin:
Cognitive Control: Theory and Application. IEEE Access 2: 698-710 (2014) - [c3]Simon Haykin, Ashkan Amiri, Mehdi Fatemi:
Cognitive control in cognitive dynamic systems: A new way of thinking inspired by the brain. ADPRL 2014: 1-7 - [i1]Mehdi Fatemi, Peyman Setoodeh, Simon Haykin:
Improving Observability of Stochastic Complex Networks under the Supervision of Cognitive Dynamic Systems. CoRR abs/1412.6162 (2014) - 2012
- [j1]Simon Haykin, Mehdi Fatemi, Peyman Setoodeh, Yanbo Xue:
Cognitive Control. Proc. IEEE 100(12): 3156-3169 (2012)
2000 – 2009
- 2009
- [c2]Mehdi Fatemi, Jim Millan, Tina Yu, Siu O'Young:
Toward a general control design paradigm for hybrid systems: Ideas, concepts, and formulations. CCECE 2009: 1158-1162 - 2005
- [c1]Mehdi Fatemi, Mehdi Roopaei, Faridoon Shabaninia:
New Enhanced Methods for Radial Basis Function Neural Networks in Function Approximation. HIS 2005: 524-527
Coauthor Index
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last updated on 2024-10-07 22:19 CEST by the dblp team
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