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
Arambam James SinghResearch Fellow, School of Computer Science Engineering, Nanyang Technological University, SingaporeVerified email at ntu.edu.sg
Marc ToussaintProfessor of Computer Science, TU Berlin, GermanyVerified email at tu-berlin.de
Xiaojian WuFacebookVerified email at cs.umass.edu
Tao SunResearch Scientist, BytedanceVerified email at bytedance.com
William YeohWashington University in St. LouisVerified email at wustl.edu
Hala MostafaRaytheon Technologies Research CenterVerified email at rtx.com
Thomas DietterichDistinguished Professor (Emeritus), Computer Science, Oregon State UniversityVerified email at cs.orst.edu
Meghna LowalekarSingapore Management UniversityVerified 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, Microsoft ResearchVerified email at microsoft.com
Pritee Agrawalsingapore management universityVerified email at phdis.smu.edu.sg
Shih-Fen ChengSchool of Computing and Information Systems, Singapore Management UniversityVerified email at smu.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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Distributed constraint optimization with structured resource constraints A Kumar, B Faltings, A Petcu IFAAMAS 2, 923, 2009	88	2009
Credit assignment for collective multiagent RL with global rewards DT Nguyen, A Kumar, HC Lau Advances in neural information processing systems 31, 2018	86	2018
Scalable multiagent planning using probabilistic inference A Kumar, S Zilberstein, M Toussaint AAAI Press, 2011	81	2011
Constraint-based dynamic programming for decentralized POMDPs with structured interactions A Kumar, S Zilberstein IFAAMS, 2009	68	2009
Approximate inference in collective graphical models D Sheldon, T Sun, A Kumar, T Dietterich International Conference on Machine Learning, 1004-1012, 2013	60	2013
Anytime planning for decentralized POMDPs using expectation maximization A Kumar, S Zilberstein arXiv preprint arXiv:1203.3490, 2012	60	2012
Point-based backup for decentralized POMPDs: Complexity and new algorithms A Kumar, S Zilberstein IFAAMAS 1, 1315, 2010	53	2010
Policy gradient with value function approximation for collective multiagent planning DT Nguyen, A Kumar, HC Lau Advances in neural information processing systems 30, 2017	51	2017
Probabilistic inference techniques for scalable multiagent decision making A Kumar, S Zilberstein, M Toussaint Journal of Artificial Intelligence Research 53, 223-270, 2015	44	2015
Collective multiagent sequential decision making under uncertainty DT Nguyen, A Kumar, HC Lau Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017	43	2017
Message passing for collective graphical models T Sun, D Sheldon, A Kumar International Conference on Machine Learning, 853-861, 2015	40	2015
Optimization approaches for solving chance constrained stochastic orienteering problems P Varakantham, A Kumar Algorithmic Decision Theory: Third International Conference, ADT 2013 …, 2013	39	2013
Tournament versus fitness uniform selection S Legg, M Hutter, A Kumar Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No …, 2004	37	2004
Event-detecting multi-agent MDPs: Complexity and constant-factor approximation A Kumar, S Zilberstein	34	2009
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	33	2022
Resource constrained deep reinforcement learning A Bhatia, P Varakantham, A Kumar Proceedings of the International Conference on Automated Planning and …, 2019	30	2019
Dynamic programming approximations for partially observable stochastic games A Kumar, S Zilberstein AAAI Press, 2009	29	2009
Lagrangian relaxation techniques for scalable spatial conservation planning A Kumar, X Wu, S Zilberstein Proceedings of the AAAI Conference on Artificial Intelligence 26 (1), 309-315, 2012	28	2012
Collective diffusion over networks: Models and inference A Kumar, D Sheldon, B Srivastava arXiv preprint arXiv:1309.6841, 2013	26	2013
H-DPOP: Using Hard Constraints for Search Space Pruning in DCOP. A Kumar, A Petcu, B Faltings AAAI, 325-330, 2008	26	2008

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