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Mamal Amini
Mamal Amini
Now @ GovernGPT.ai | ex Cerebras | ex Huawei | ex Mila | McGill alumn
Verified email at mail.mcgill.ca
Title
Cited by
Cited by
Year
Patchup: A feature-space block-level regularization technique for convolutional neural networks
M Faramarzi, M Amini, A Badrinaaraayanan, V Verma, S Chandar
Proceedings of the AAAI Conference on Artificial Intelligence 36 (1), 589-597, 2022
592022
The applicability of genetic algorithm to vertex cover
H Bhasin, M Amini
International Journal of Computer Applications 123 (17), 29-34, 2015
112015
Generalizable floorplanner through corner block list representation and hypergraph embedding
M Amini, Z Zhang, S Penmetsa, Y Zhang, J Hao, W Liu
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
82022
Towered actor critic for handling multiple action types in reinforcement learning for drug discovery
SK Gottipati, Y Pathak, B Sattarov, R Nuttall, M Amini, ME Taylor, ...
Proceedings of the AAAI Conference on Artificial Intelligence 35 (1), 142-150, 2021
72021
Dealing with non-stationarity in decentralized cooperative multi-agent deep reinforcement learning via multi-timescale learning
H Nekoei, A Badrinaaraayanan, A Sinha, M Amini, J Rajendran, ...
Conference on Lifelong Learning Agents, 376-398, 2023
62023
Staged independent learning: Towards decentralized cooperative multi-agent reinforcement learning
H Nekoei, A Badrinaaraayanan, A Sinha, M Amini, J Rajendran, ...
ICLR 2022 Workshop on Gamification and Multiagent Solutions, 2022
12022
On the applicability of Diploid Genetic Algorithms in Vertex Cover Problem
M Amini, S Dwivedi, MA Beg
CSI transactions on ICT 4, 177-182, 2016
12016
Improving Sample Efficiency of Value Based Models Using Attention and Vision Transformers
A Ardalan Kalantari, M Amini, S Chandar, D Precup
arXiv e-prints, arXiv: 2202.00710, 2022
2022
Policy Guided Planning in Learned Latent Space for Model-based Reinforcement Learning
M Amini
McGill University (Canada), 2021
2021
Policy Guided Planning in Latent Space
M Amini, D Precup, S Chandar
Deep Reinforcement Learning Workshop, https://drive.google.com/file/d/1IVK9FNz, 2020
2020
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Articles 1–10