Ishan Durugkar

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Peter StoneProfessor of Computer Science, The University of Texas at AustinVerified email at cs.utexas.edu
Sridhar MahadevanDirector, Data Science Lab, Adobe Research & Professor, University of Massachusetts, AmherstVerified email at cs.umass.edu
Ian GempGoogle DeepMindVerified email at google.com
Rajarshi DasAWS AI LabsVerified email at cs.washington.edu
Luke VilnisResearch Scientist, Google DeepMindVerified email at google.com
Shehzaad DhuliawalaETH ZurichVerified email at inf.ethz.ch
Akshay KrishnamurthyUniversity of Massachusetts AmherstVerified email at cs.umass.edu
Andrew McCallumDistinguished Professor of Computer Science, University of Massachusetts AmherstVerified email at cs.umass.edu
Alex SmolaBoson AIVerified email at smola.org
Manzil ZaheerGoogle ResearchVerified email at cmu.edu
Josiah P. HannaAssistant Professor, University of Wisconsin--MadisonVerified email at cs.wisc.edu
Garrett WarnellResearch Scientist, Army Research LaboratoryVerified email at army.mil
Mauricio TecHarvard UniversityVerified email at hsph.harvard.edu
Elad LiebmanApplied Scientist, Amazon & Assistant Prof. of Instruction, UT AustinVerified email at cs.utexas.edu
Dr Anand J KulkarniProfessor & Associate Director, Institute of Artificial Intelligence, Dr Vishwanath Karad MIT WorldVerified email at ntu.edu.sg
Haresh KarnanPh.D., The University of Texas at AustinVerified email at utexas.edu
Philip ThomasUniversity of Massachusetts AmherstVerified email at cs.umass.edu
Emma BrunskillAssociate Professor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
Georgios TheocharousAdobe ResearchVerified email at adobe.com
Scott NiekumAssociate Professor, University of Massachusetts AmherstVerified email at cs.umass.edu

Ishan Durugkar

Research Scientist, Sony AI

Verified email at sony.com - Homepage

Reinforcement Learning Generative Models Machine Learning Multi-agent systems Artificial Intelligence


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Go for a walk and arrive at the answer: Reasoning over paths in knowledge bases using reinforcement learning R Das, S Dhuliawala, M Zaheer, L Vilnis, I Durugkar, A Krishnamurthy, ... arXiv preprint arXiv:1711.05851, 2017	608	2017
Generative Multi-Adversarial Networks I Durugkar, I Gemp, S Mahadevan International Conference on Learning Representations, 2017, 2017	465	2017
Cohort intelligence: a self supervised learning behavior AJ Kulkarni, IP Durugkar, M Kumar 2013 IEEE international conference on systems, man, and cybernetics, 1396-1400, 2013	135	2013
Predictive off-policy policy evaluation for nonstationary decision problems, with applications to digital marketing P Thomas, G Theocharous, M Ghavamzadeh, I Durugkar, E Brunskill Proceedings of the AAAI Conference on Artificial Intelligence 31 (2), 4740-4745, 2017	68	2017
An imitation from observation approach to transfer learning with dynamics mismatch S Desai, I Durugkar, H Karnan, G Warnell, J Hanna, P Stone Advances in Neural Information Processing Systems 33, 3917-3929, 2020	50	2020
Adversarial intrinsic motivation for reinforcement learning I Durugkar, M Tec, S Niekum, P Stone Advances in Neural Information Processing Systems 34, 8622-8636, 2021	37	2021
Deep reinforcement learning with macro-actions IP Durugkar, C Rosenbaum, S Dernbach, S Mahadevan arXiv preprint arXiv:1606.04615, 2016	28	2016
Balancing individual preferences and shared objectives in multiagent reinforcement learning I Durugkar, E Liebman, P Stone International Joint Conference on Artificial Intelligence, 2020	22	2020
Reducing sampling error in batch temporal difference learning B Pavse, I Durugkar, J Hanna, P Stone International Conference on Machine Learning, 7543-7552, 2020	15	2020
TD learning with constrained gradients I Durugkar, P Stone	15	2018
Towards a real-time, low-resource, end-to-end object detection pipeline for robot soccer SK Narayanaswami, M Tec, I Durugkar, S Desai, B Masetty, S Narvekar, ... Robot World Cup, 62-74, 2022	7	2022
Wasserstein distance maximizing intrinsic control I Durugkar, S Hansen, S Spencer, V Mnih arXiv preprint arXiv:2110.15331, 2021	4	2021
An imitation from observation approach to sim-to-real transfer S Desai, I Durugkar, H Karnan, G Warnell, J Hanna, P Stone, A Sony 2nd Workshop on Closing the Reality Gap in Sim2Real Transfer for Robotics. RSS, 2020	3	2020
Unmixing in the presence of nuisances with deep generative models M Parente, I Gemp, I Durugkar 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS …, 2017	3	2017
f-Policy Gradients: A General Framework for Goal-Conditioned RL using f-Divergences S Agarwal, I Durugkar, P Stone, A Zhang Advances in Neural Information Processing Systems 36, 2024	2	2024
Abc: Adversarial behavioral cloning for offline mode-seeking imitation learning E Hudson, I Durugkar, G Warnell, P Stone arXiv preprint arXiv:2211.04005, 2022	2	2022
DM : Distributed multi-agent reinforcement learning via distribution matching C Wang	2	2022
Multi-preference actor critic I Durugkar, M Hausknecht, A Swaminathan, P MacAlpine arXiv preprint arXiv:1904.03295, 2019	2	2019
Adversarial goal generation for intrinsic motivation I Durugkar, P Stone Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018	2	2018
Inverting variational autoencoders for improved generative accuracy I Gemp, I Durugkar, M Parente, MD Dyar, S Mahadevan arXiv preprint arXiv:1608.05983, 2016	2	2016

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