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Avishek Ghosh
Avishek Ghosh
Assistant Professor, IIT Bombay
Verified email at iitb.ac.in - Homepage
Title
Cited by
Cited by
Year
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
2802020
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
1282019
Misspecified Linear Bandits
A Ghosh, S Ray Chowdhury, A Gopalan
Thirty-First AAAI Conference on Artificial Intelligence, 2017
462017
Problem-Complexity Adaptive Model Selection for Stochastic Linear Bandits
A Ghosh, A Sankararaman, K Ramchandran
International Conference on Artificial Intelligence and Statistics (AISTATS†…, 2021
242021
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
232019
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
222013
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
222012
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
172020
Communication Efficient Distributed Approximate Newton Method
A Ghosh, RK Maity, A Mazumdar, K Ramchandran
IEEE International Symposium on Information Theory (ISIT), 2020, 2020
172020
Alternating Minimization Converges Super-linearly for Mixed Linear Regression
A Ghosh, K Ramchandran
International Conference on Artificial Intelligence and Statistics (AISTATS†…, 2020
142020
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
132021
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
102020
Impromptu Deployment of Wireless Relay Networks: Experiences Along a Forest Trail
A Chattopadhyay, A Ghosh, AS Rao, B Dwivedi, SVR Anand, ...
Mobile Ad Hoc and Sensor Systems (MASS), 2014, arXiv preprint arXiv:1409†…, 2014
92014
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
8*2022
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
72021
Linear phase low pass FIR filter design using genetic particle swarm optimization with dynamically varying neighbourhood technique
A Ghosh, A Ghosh, A Chowdhury, A Konar, E Kim, AK Nagar
2012 IEEE Congress on Evolutionary Computation, 1-7, 2012
72012
Integral Value Transformations: A Class of Affine Discrete Dynamical Systems and an Application
SS Hassan, PP Choudhury, BK Nayak, A Ghosh, J Banerjee
Journal of Advanced Research in Applied Mathematics, Preprint arXiv:1110.0724, 2011
72011
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
62021
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
62021
Model Selection for Generic Contextual Bandits
A Ghosh, A Sankararaman, K Ramchandran
arXiv Preprint: https://arxiv.org/pdf/2107.03455.pdf, 2021
52021
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Articles 1–20