Vatsal Shah

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Citations	178	159
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Sujay SanghaviAssociate Professor, Electrical and Computer Engineering, University of Texas, AustinVerified email at mail.utexas.edu
Anastasios KyrillidisAssociate Professor, Computer Science Department, Ken Kennedy Institute Fellow, Rice UniversityVerified email at rice.edu
Krishna Mohan BuddhirajuProfessor at CSRE, IIT Bombay, IndiaVerified email at csre.iitb.ac.in
Ashish KatiyarUniversity of Texas at AustinVerified email at utexas.edu
Constantine CaramanisProfessor of Electrical and Computer Engineering, UT AustinVerified email at utexas.edu
Dr. Biplab BanerjeeAssociate Professor, CSRE, CMInDS, Indian Institute of Technology MumbaiVerified email at iitb.ac.in
Xiaoxia (Shirley) Wu 吴晓霞MicrosoftVerified email at microsoft.com
John ChenRice UniversityVerified email at rice.edu
Nikhil RaoMicrosoftVerified email at microsoft.com
Surender VarmaUPESVerified email at ddn.upes.ac.in
Soumya BasuML Engineer, GoogleVerified email at google.com
Megasthenis AsterisUniversity of Texas at AustinVerified email at utexas.edu
Alexandros G DimakisProfessor, ECE University of Texas at AustinVerified email at austin.utexas.edu
Yanyao ShenUniversity of Texas at AustinVerified email at utexas.edu
Erik M LindgrenGoogleVerified email at google.com
Adam KlivansProfessor of Computer Science, University of Texas at AustinVerified email at cs.utexas.edu
Weicong DingScientist at Roku Inc.

Vatsal Shah

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Stochastic Optimization Optimization and Algorithms Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Choosing the Sample with Lowest Loss makes SGD Robust V Shah, X Wu, S Sanghavi Proceedings of the Twenty Third International Conference on Artificial …, 2020	49	2020
Negative sampling in semi-supervised learning J Chen, V Shah, A Kyrillidis International Conference on Machine Learning, 1704-1714, 2020	28	2020
Minimum norm solutions do not always generalize well for over-parameterized problems V Shah, A Kyrillidis, S Sanghavi In NeurIPS Workshop on Integration of Deep Learning Theories, 2019., 2018	24*	2018
Change detection of desert sand dunes: a remote sensing approach S Varma, V Shah, B Banerjee, KM Buddhiraju Advances in remote sensing 3 (01), 10, 2014	23	2014
Trading-off variance and complexity in stochastic gradient descent V Shah, M Asteris, A Kyrillidis, S Sanghavi arXiv preprint arXiv:1603.06861, 2016	14	2016
Robust estimation of tree structured ising models A Katiyar, V Shah, C Caramanis arXiv preprint arXiv:2006.05601, 2020	11	2020
Matrix factorization with side and higher order information V Shah, N Rao, W Ding In 13th International KDD Workshop on Mining and Learning with Graphs, 2017., 2017	10*	2017
On Robust Learning of Ising Models AK Erik Lindgren, Vatsal Shah, Yanyao Shen, Alex Dimakis In Relational Representation Learning Workshop at NeurIPS 2019, 2018	9*	2018
Segmentation of desert sand dunes SV Gadhiraju, V Shah, KM Buddhiraju Remote sensing letters 5 (11), 961-970, 2014	7	2014
Robust estimation of tree structured markov random fields A Katiyar, S Basu, V Shah, C Caramanis arXiv preprint arXiv:2102.08554, 2021	2	2021
On Variants of Stochastic Gradient Descent VN Shah The University of Texas at Austin, 2020	1	2020
Power of Choices: Performance under Error and Compression S Basu, V Shah		2015
Polynomial Time Approximation Schemes for the Euclidean Traveling Salesman Problem S Wu, V Shah		2015
Unchanging Desert Sand Dunes S Gadhiraju, B Banerjee, K Buddhiraju, V Shah AGU Fall Meeting Abstracts 2013, V21A-2697, 2013		2013

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