Avishek Ghosh

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Kannan RamchandranProfessor of Electrical Engineering and Computer Science, UC BerkeleyVerificeret mail på eecs.berkeley.edu
Arya MazumdarUniversity of California, San DiegoVerificeret mail på ucsd.edu
Dong YinResearch Scientist, AppleVerificeret mail på apple.com
Raj Kumar MaityMicrosoft & CICS, University of Massachusetts, AmherstVerificeret mail på cs.umass.edu
Abishek SankararamanML Scientist, AWSVerificeret mail på amazon.com
Sayak Ray ChowdhuryAssistant Professor of Computer Science and Engineering, Indian Institute of Technology, KanpurVerificeret mail på cse.iitk.ac.in
Aditya GopalanIndian Institute of Science, BangaloreVerificeret mail på iisc.ac.in
Amit KonarProfessor of Electronics and Tele-Communication Department, Jadavpur UniversityVerificeret mail på etce.jdvu.ac.in
Anurag KumarHonorary Professor, ECE Department, Indian Institute of ScienceVerificeret mail på iisc.ac.in
Arpan ChattopadhyayIndian Institute of Technology DelhiVerificeret mail på ee.iitd.ac.in
Adityanand GuntuboyinaAssociate Professor, Department of Statistics, University of California, BerkeleyVerificeret mail på stat.berkeley.edu
Pabitra Pal ChoudhuryProfessor in Applied Statistics Unit, Indian Statistical Institute, KolkataVerificeret mail på isical.ac.in
Swagatam DasProfessor, Electronics and Communication Sciences Unit, Indian Statistical Institute, KolkataVerificeret mail på isical.ac.in
Anish AroraChair & Distinguished Professor, Computer Science & Engg., Ohio State; Founder, Samraksh CompanyVerificeret mail på cse.ohio-state.edu
Sk. Sarif HassanAssistant Professor, Department of Mathematics, Pingla Thana Mahavidyalaya, West Bengal, IndiaVerificeret mail på pinglacollege.ac.in
Abhay Parekh(Ex) Adjunct Professor, Electrical Engineering and Computer Science, U C BerkeleyVerificeret mail på eecs.berkeley.edu
Sunita SarawagiIndian Institute of Technology Bombay, Mumbai, India.Verificeret mail på iitb.ac.in
Debasish ChatterjeeProfessor, Systems & Control Engineering, IIT-BombayVerificeret mail på iitb.ac.in

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Avishek Ghosh

Assistant Professor, Dept. of Computer Science & Engg., IIT Bombay

Verificeret mail på iitb.ac.in - Startside

Theoretical Machine Learning Optimization RL Bandits


Titel Sortér efter henvisninger Sortér efter årstal Sortér efter titel	Citeret af Citeret af	År
An Efficient Framework for Clustered Federated Learning A Ghosh, J Chung, D Yin, K Ramchandran Neural Information Processing Systems (NeurIPS), 2020 (short version in ICML …, 2020	951	2020
Robust Federated Learning in a Heterogeneous Environment A Ghosh, J Hong, D Yin, K Ramchandran ICML 2019 workshop on Privacy and Security, 1-30, 2019	289	2019
An efficient framework for clustered federated learning A Ghosh, J Chung, D Yin, K Ramchandran IEEE Transactions on Information Theory 68 (12), 8076-8091, 2022	148	2022
Misspecified Linear Bandits A Ghosh, S Ray Chowdhury, A Gopalan Thirty-First AAAI Conference on Artificial Intelligence, 2017	75	2017
Distributed Newton Can Communicate Less and Resist Byzantine Workers A Ghosh, RK Maity, A Mazumdar Neural Information Processing Systems (NeurIPS), 2020 (short version in ICML …, 2020	40	2020
Problem-Complexity Adaptive Model Selection for Stochastic Linear Bandits A Ghosh, A Sankararaman, K Ramchandran International Conference on Artificial Intelligence and Statistics (AISTATS …, 2021	36	2021
Max-Affine Regression: Provable, Tractable, and Near-Optimal Statistical Estimation A Ghosh, A Pananjady, A Guntuboyina, K Ramchandran IEEE Transactions on Information Theory; Preprint: http://arxiv.org/abs/1906 …, 2019	33	2019
Multi-robot cooperative box-pushing problem using multi-objective particle swarm optimization Technique A Ghosh, A Ghosh, A Konar, R Janarthanan Information and Communication Technologies (WICT), 2012 World Congress on …, 2012	31	2012
Alternating Minimization Converges Super-linearly for Mixed Linear Regression A Ghosh, K Ramchandran International Conference on Artificial Intelligence and Statistics (AISTATS …, 2020	30	2020
Communication-efficient and byzantine-robust distributed learning with error feedback A Ghosh, RK Maity, S Kadhe, A Mazumdar, K Ramchandran IEEE Journal on Selected Areas in Information Theory 2 (3), 942-953, 2021	29	2021
Communication Efficient Distributed Approximate Newton Method A Ghosh, RK Maity, A Mazumdar, K Ramchandran IEEE International Symposium on Information Theory (ISIT), 2020, 2020	27	2020
Communication-efficient and byzantine-robust distributed learning A Ghosh, RK Maity, S Kadhe, A Mazumdar, K Ramchandran Preprint: https://arxiv.org/pdf/1911.09721.pdf (short version in 2020 ITA), 2021	26	2021
Max-affine regression: Parameter estimation for Gaussian designs A Ghosh, A Pananjady, A Guntuboyina, K Ramchandran IEEE Transactions on Information Theory 68 (3), 1851-1885, 2021	25	2021
A novel genetic algorithm to solve travelling salesman problem and blocking flow shop scheduling problem A Chowdhury, A Ghosh, S Sinha, S Das, A Ghosh International Journal of Bio-Inspired Computation 5 (5), 303-314, 2013	23	2013
LocalNewton: Reducing Communication Bottleneck for Distributed Learning V Gupta, A Ghosh, M Derezinski, R Khanna, K Ramchandran, M Mahoney Preprint: https://arxiv.org/pdf/2105.07320.pdf, 2021	17	2021
Communication Efficient and Byzantine Tolerant Distributed Learning A Ghosh, RK Maity, S Kadhe, A Mazumdar, K Ramchandran IEEE International Symposium on Information Theory (ISIT), 2020, 2020	17	2020
Understanding and Control of Zener Pinning via Phase Field and Ensemble Learning S Manna, H Chan, A Ghosh, T Chakraborti, S Sankaranarayanan Computational Materials Science, 2023	14	2023
On learning mixture of linear regressions in the non-realizable setting A Ghosh, A Mazumdar, S Pal, R Sen International Conference on Machine Learning, 17202-17220, 2022	14	2022
Competing Bandits in Non-Stationary Matching Markets A Ghosh, A Sankararaman, K Ramchandran, T Javidi, A Mazumdar IEEE Transactions on Information Theory, 2024	13*	2024
Collaborative Learning and Personalization in Multi-Agent Stochastic Linear Bandits A Ghosh, A Sankararaman, K Ramchandran European Conference on Machine Learning (ECML-PKDD 2022), arXiv Preprint …, 2022	10	2022

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