Activité

  • Étudiant à la maitrise: jan. 2020 - juil. 2021

Thèse de maitrise

  1. Continuous Coordination As a Realistic Scenario for Lifelong Learning
    par Akilesh Badrinaaraayanan, avec Aaron Courville et Sarath Chandar comme superviseurs.
    Université de Montréal, avril 2021.
    [thesis]

Articles de conférence et de revue

2023

  1. Dealing With Non-stationarity in Decentralized Cooperative Multi-Agent Deep Reinforcement Learning via Multi-Timescale Learning
    Hadi Nekoei, Akilesh Badrinaaraayanan, Amit Sinha, Mohammad Amini, Janarthanan Rajendran, Aditya Mahajan et Sarath Chandar
    Conference on Lifelong Learning Agents (CoLLAs), 2023.
    #RL
    [arXiv]

2022

  1. PatchUp: A Feature-Space Block-Level Regularization Technique for Convolutional Neural Networks
    Mojtaba Faramarzi, Mohammad Amini, Akilesh Badrinaaraayanan, Vikas Verma et Sarath Chandar
    AAAI Conference on Artificial Intelligence (AAAI), 2022.
    #DL
    [arXiv], [code]

2021

  1. Continuous Coordination As a Realistic Scenario for Lifelong Learning
    Hadi Nekoei, Akilesh Badrinaaraayanan, Aaron Courville et Sarath Chandar
    International Conference on Machine Learning (ICML), 2021.
    #RL
    [arXiv], [code]