Akshat Kumar

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Shlomo ZilbersteinProfessor of Computer Science, University of Massachusetts AmherstVerified email at cs.umass.edu
Pradeep VarakanthamProfessor of Computer Science, Lee Kuan Yew Fellow, Director of CARE.AI lab, School of Computing andVerified email at smu.edu.sg
Daniel SheldonUniversity of Massachusetts AmherstVerified email at cs.umass.edu
Marc ToussaintProfessor of Computer Science, TU Berlin, GermanyVerified email at tu-berlin.de
Xiaojian WuFacebookVerified email at cs.umass.edu
Tao SunResearch Scientist, Bytedance, ex-AmazonVerified email at bytedance.com
William YeohWashington University in St. LouisVerified email at wustl.edu
Hala MostafaBitsight TechnologiesVerified email at bitsight.com
Thomas DietterichDistinguished Professor (Emeritus), Computer Science, Oregon State UniversityVerified email at cs.orst.edu
Meghna LowalekarData Science Consultant at THBVerified email at phdis.smu.edu.sg
Shivashankar B NairProfessor, Dept. of Computer Science & Engg., Indian Institute of Technology GuwahatiVerified email at iitg.ernet.in
Supriyo GhoshSenior Researcher, MicrosoftVerified email at microsoft.com
Pritee Agrawalsingapore management universityVerified email at phdis.smu.edu.sg
Shih-Fen ChengAmazon / School of Computing and Information Systems, Singapore Management UniversityVerified email at smu.edu.sg
James ArambamResearch Fellow, School of Computer Science Engineering, Nanyang Technological University, SingaporeVerified email at ntu.edu.sg

Akshat Kumar

Associate Professor, School of Information Systems, Singapore Management

Verified email at smu.edu.sg - Homepage

Artificial Intelligence Machine learning


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Cost: Contrastive learning of disentangled seasonal-trend representations for time series forecasting G Woo, C Liu, D Sahoo, A Kumar, S Hoi arXiv preprint arXiv:2202.01575, 2022	247	2022
Etsformer: Exponential smoothing transformers for time-series forecasting G Woo, C Liu, D Sahoo, A Kumar, S Hoi arXiv preprint arXiv:2202.01381, 2022	193	2022
Credit assignment for collective multiagent RL with global rewards DT Nguyen, A Kumar, HC Lau Advances in neural information processing systems 31, 2018	118	2018
Distributed constraint optimization with structured resource constraints A Kumar, B Faltings, A Petcu IFAAMAS 2, 923, 2009	91	2009
Scalable multiagent planning using probabilistic inference A Kumar, S Zilberstein, M Toussaint AAAI Press, 2011	84	2011
Constraint-based dynamic programming for decentralized POMDPs with structured interactions A Kumar, S Zilberstein IFAAMS, 2009	72	2009
Approximate inference in collective graphical models D Sheldon, T Sun, A Kumar, T Dietterich International Conference on Machine Learning, 1004-1012, 2013	65	2013
Policy gradient with value function approximation for collective multiagent planning DT Nguyen, A Kumar, HC Lau Advances in neural information processing systems 30, 2017	62	2017
Anytime planning for decentralized POMDPs using expectation maximization A Kumar, S Zilberstein arXiv preprint arXiv:1203.3490, 2012	61	2012
Resource constrained deep reinforcement learning A Bhatia, P Varakantham, A Kumar Proceedings of the International Conference on Automated Planning and …, 2019	54	2019
Collective multiagent sequential decision making under uncertainty DT Nguyen, A Kumar, HC Lau Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017	52	2017
Point-based backup for decentralized POMPDs: Complexity and new algorithms A Kumar, S Zilberstein IFAAMAS 1, 1315, 2010	52	2010
Probabilistic inference techniques for scalable multiagent decision making A Kumar, S Zilberstein, M Toussaint Journal of Artificial Intelligence Research 53, 223-270, 2015	50	2015
Optimization approaches for solving chance constrained stochastic orienteering problems P Varakantham, A Kumar Algorithmic Decision Theory: Third International Conference, ADT 2013 …, 2013	50	2013
Tournament versus fitness uniform selection S Legg, M Hutter, A Kumar Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No …, 2004	42	2004
Message passing for collective graphical models T Sun, D Sheldon, A Kumar International Conference on Machine Learning, 853-861, 2015	41	2015
Dynamic programming approximations for partially observable stochastic games A Kumar, S Zilberstein Twenty-Second International FLAIRS Conference, 2009	39	2009
Unified training of universal time series forecasting transformers G Woo, C Liu, A Kumar, C Xiong, S Savarese, D Sahoo arXiv preprint arXiv:2402.02592, 2024	35	2024
Hierarchical multiagent reinforcement learning for maritime traffic management AJ Singh, A Kumar, HC Lau IFAAMAS, 2020	35	2020
Event-detecting multi-agent MDPs: Complexity and constant-factor approximation A Kumar, S Zilberstein	35	2009

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