Gautam Kamath
Gautam Kamath
Assistant Professor, University of Waterloo
Verified email at csail.mit.edu - Homepage
Title
Cited by
Cited by
Year
Robust estimators in high-dimensions without the computational intractability
I Diakonikolas, G Kamath, D Kane, J Li, A Moitra, A Stewart
SIAM Journal on Computing 48 (2), 742-864, 2019
2032019
Optimal testing for properties of distributions
J Acharya, C Daskalakis, G Kamath
Advances in Neural Information Processing Systems, 3591-3599, 2015
1092015
Being robust (in high dimensions) can be practical
I Diakonikolas, G Kamath, DM Kane, J Li, A Moitra, A Stewart
arXiv preprint arXiv:1703.00893, 2017
942017
Sever: A robust meta-algorithm for stochastic optimization
I Diakonikolas, G Kamath, D Kane, J Li, J Steinhardt, A Stewart
International Conference on Machine Learning, 1596-1606, 2019
922019
Robustly learning a gaussian: Getting optimal error, efficiently
I Diakonikolas, G Kamath, DM Kane, J Li, A Moitra, A Stewart
Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete …, 2018
712018
Faster and Sample Near-Optimal Algorithms for Proper Learning Mixtures of Gaussians
C Daskalakis, G Kamath
Proceedings of the 27th Annual Conference on Learning Theory, 1183-1213, 2014
662014
Testing ising models
C Daskalakis, N Dikkala, G Kamath
IEEE Transactions on Information Theory 65 (11), 6829-6852, 2019
582019
An Analysis of One-Dimensional Schelling Segregation
C Brandt, N Immorlica, G Kamath, R Kleinberg
Proceedings of the 44th Annual ACM Symposium on the Theory of Computing, 789-804, 2012
552012
Priv'it: Private and sample efficient identity testing
B Cai, C Daskalakis, G Kamath
arXiv preprint arXiv:1703.10127, 2017
322017
A size-free CLT for poisson multinomials and its applications
C Daskalakis, A De, G Kamath, C Tzamos
Proceedings of the forty-eighth annual ACM symposium on Theory of Computing …, 2016
302016
Privately learning high-dimensional distributions
G Kamath, J Li, V Singhal, J Ullman
Conference on Learning Theory, 1853-1902, 2019
292019
Which distribution distances are sublinearly testable?
C Daskalakis, G Kamath, J Wright
Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete …, 2018
252018
A chasm between identity and equivalence testing with conditional queries
J Acharya, CL Canonne, G Kamath
arXiv preprint arXiv:1411.7346, 2014
232014
The structure of optimal private tests for simple hypotheses
CL Canonne, G Kamath, A McMillan, A Smith, J Ullman
Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing …, 2019
222019
On the structure, covering, and learning of poisson multinomial distributions
C Daskalakis, G Kamath, C Tzamos
2015 IEEE 56th Annual Symposium on Foundations of Computer Science, 1203-1217, 2015
202015
INSPECTRE: Privately Estimating the Unseen
J Acharya, G Kamath, Z Sun, H Zhang
Journal of Privacy and Confidentiality 10 (2), 2020
172020
Concentration of multilinear functions of the Ising model with applications to network data
C Daskalakis, N Dikkala, G Kamath
Advances in Neural Information Processing Systems, 12-23, 2017
162017
Bounds on the expectation of the maximum of samples from a gaussian
G Kamath
URL http://www. gautamkamath. com/writings/gaussian max. pdf, 2015
152015
Private identity testing for high-dimensional distributions
CL Canonne, G Kamath, A McMillan, J Ullman, L Zakynthinou
arXiv preprint arXiv:1905.11947, 2019
122019
Private hypothesis selection
M Bun, G Kamath, T Steinke, SZ Wu
Advances in Neural Information Processing Systems, 156-167, 2019
102019
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