Anuj Mahajan
Anuj Mahajan
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Maven: Multi-agent variational exploration
A Mahajan, T Rashid, M Samvelyan, S Whiteson
arXiv preprint arXiv:1910.07483, 2019
Virel: A variational inference framework for reinforcement learning
M Fellows, A Mahajan, TGJ Rudner, S Whiteson
Advances in Neural Information Processing Systems 32, 7122-7136, 2019
Symmetry learning for function approximation in reinforcement learning
A Mahajan, T Tulabandhula
arXiv preprint arXiv:1706.02999, 2017
Feature selection for short text classification using Wavelet Packet Transform
A Mahajan, S Jat, S Roy
Proceedings of the Nineteenth Conference on Computational Natural Language …, 2015
Symmetry detection and exploitation for function approximation in deep rl
A Mahajan, T Tulabandhula
Proceedings of the 16th Conference on Autonomous Agents and MultiAgent …, 2017
Variational task embeddings for fast adapta-tion in deep reinforcement learning
L Zintgraf, M Igl, K Shiarlis, A Mahajan, K Hofmann, S Whiteson
International Conference on Learning Representations Workshop (ICLRW), 2019
Lifted inference rules with constraints
H Mittal, A Mahajan, VG Gogate, P Singla
Advances in Neural Information Processing Systems 28, 3519-3527, 2015
Method and system for predicting requirements of a user for resources over a computer network
S Jat, A Mahajan, S Roy
US Patent 10,417,578, 2019
RODE: Learning Roles to Decompose Multi-Agent Tasks
T Wang, T Gupta, A Mahajan, B Peng, S Whiteson, C Zhang
arXiv preprint arXiv:2010.01523, 2020
UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning
T Gupta, A Mahajan, B Peng, W Böhmer, S Whiteson
arXiv preprint arXiv:2010.02974, 2020
Personalizing application interfaces based on usage
S Srivastava, K Simarjot, T Bhattacharya, L Nupur, J Macurak, A Mahajan, ...
US Patent App. 15/986,161, 2019
Supplementary Material: Lifted Inference Rules with Constraints
H Mittal, A Mahajan, V Gogate, P Singla
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