Shubhanshu Shekhar

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Tara JavidiLewak Endowed Chair and Professor of Electrical and Computer Engineering, UCSDVerified email at ucsd.edu
Aaditya RamdasAssociate Professor, Statistics and Machine Learning, Carnegie Mellon UniversityVerified email at stat.cmu.edu
Mohammad GhavamzadehAmazon AGIVerified email at amazon.com
Farinaz KoushanfarProfessor and Siavouche Nemat-Nasser Endowed Chair of ECE, UC San DiegoVerified email at ucsd.edu
Anusha LalithaAmazon AWS AI LabsVerified email at amazon.com
Ilmun KimYonsei UniversityVerified email at yonsei.ac.kr
Greg FieldsPhD Student, UC San DiegoVerified email at ucsd.edu
Sebastien RochProfessor of Mathematics, UW MadisonVerified email at math.wisc.edu
Siavash MirarabUniversity of California at San DiegoVerified email at ucsd.edu
Matteo PirottaResearch Scientist, Meta (FAIR)Verified email at fb.com
Jean TarbouriechGoogle DeepMindVerified email at google.com
Alessandro LazaricResearch Scientist, Facebook Artificial Intelligence ResearchVerified email at inria.fr
Mohammad Javad KhojastehRochester Institute of TechnologyVerified email at rit.edu
Chuchu FanAssociate Professor of Aeronautics and Astronautics at MITVerified email at mit.edu
Dawei SunUniversity of Illinois Urbana-ChampaignVerified email at illinois.edu
Zachary C. LiptonRaj Reddy Associate Professor of Machine Learning @ Carnegie Mellon University; CTO + CSO @ AbridgeVerified email at cmu.edu
Pierre Jinghong LiangProfessor of Accounting, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
Ziyu XuCarnegie Mellon UniversityVerified email at cs.cmu.edu
Patrick ForréAssociate Professor Machine Learning, AI4Science Lab Manager, University of AmsterdamVerified email at uva.nl
Teodora PandevaUniversity of AmsterdamVerified email at uva.nl

Shubhanshu Shekhar

University of Michigan

Verified email at umich.edu - Homepage

Machine Learning Statistics


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Fully decentralized federated learning A Lalitha, S Shekhar, T Javidi, F Koushanfar Third workshop on bayesian deep learning (NeurIPS) 2, 2018	220	2018
Gaussian process bandits with adaptive discretization S Shekhar, T Javidi	47	2018
Adaptive sampling for minimax fair classification S Shekhar, G Fields, M Ghavamzadeh, T Javidi Advances in Neural Information Processing Systems 34, 24535-24544, 2021	46	2021
Species tree estimation using ASTRAL: how many genes are enough? S Shekhar, S Roch, S Mirarab IEEE/ACM transactions on computational biology and bioinformatics 15 (5 …, 2017	37	2017
Active model estimation in markov decision processes J Tarbouriech, S Shekhar, M Pirotta, M Ghavamzadeh, A Lazaric Conference on Uncertainty in Artificial Intelligence, 1019-1028, 2020	29	2020
Nonparametric two-sample testing by betting S Shekhar, A Ramdas IEEE Transactions on Information Theory, 2023	28	2023
Active learning for classification with abstention S Shekhar, M Ghavamzadeh, T Javidi IEEE Journal on Selected Areas in Information Theory 2 (2), 705-719, 2021	23	2021
A permutation-free kernel two-sample test S Shekhar, I Kim, A Ramdas Advances in Neural Information Processing Systems 35, 18168-18180, 2022	22	2022
Significance of gradient information in bayesian optimization S Shekhar, T Javidi International Conference on Artificial Intelligence and Statistics, 2836-2844, 2021	20	2021
On the near-optimality of betting confidence sets for bounded means S Shekhar, A Ramdas arXiv preprint arXiv:2310.01547, 2023	19	2023
Multiscale gaussian process level set estimation S Shekhar, T Javidi The 22nd International Conference on Artificial Intelligence and Statistics …, 2019	17	2019
Multi-scale zero-order optimization of smooth functions in an RKHS S Shekhar, T Javidi arXiv preprint arXiv:2005.04832, 2020	13	2020
Uncertain-aware safe exploratory planning using Gaussian process and neural control contraction metric D Sun, MJ Khojasteh, S Shekhar, C Fan Learning for Dynamics and Control, 728-741, 2021	12	2021
Binary classification with bounded abstention rate S Shekhar, M Ghavamzadeh, T Javidi arXiv preprint arXiv:1905.09561, 2019	10	2019
A permutation-free kernel independence test S Shekhar, I Kim, A Ramdas Journal of Machine Learning Research 24 (369), 1-68, 2023	9	2023
Multi-scale zero-order optimization of smooth functions in an RKHS M Lee, S Shekhar, T Javidi 2022 IEEE International Symposium on Information Theory (ISIT), 288-293, 2022	9	2022
Adaptive sampling for estimating probability distributions S Shekhar, T Javidi, M Ghavamzadeh International Conference on Machine Learning, 8687-8696, 2020	8	2020
Active learning for binary classification with abstention S Shekhar, M Ghavamzadeh, T Javidi arXiv preprint arXiv:1906.00303, 2019	6	2019
Instance dependent regret analysis of kernelized bandits S Shekhar, T Javidi International Conference on Machine Learning, 19747-19772, 2022	5	2022
Sequential changepoint detection via backward confidence sequences S Shekhar, A Ramdas International Conference on Machine Learning, 30908-30930, 2023	4	2023

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