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Vikrant Singhal
Vikrant Singhal
Research Associate, Harvard University
Verified email at seas.harvard.edu - Homepage
Title
Cited by
Cited by
Year
Privately learning high-dimensional distributions
G Kamath, J Li, V Singhal, J Ullman
Conference on Learning Theory, 1853-1902, 2019
1652019
Private mean estimation of heavy-tailed distributions
G Kamath, V Singhal, J Ullman
Conference on Learning Theory, 2204-2235, 2020
1072020
Differentially private algorithms for learning mixtures of separated gaussians
G Kamath, O Sheffet, V Singhal, J Ullman
Advances in Neural Information Processing Systems 32, 2019
612019
Deterministic and probabilistic binary search in graphs
E Emamjomeh-Zadeh, D Kempe, V Singhal
Proceedings of the forty-eighth annual ACM symposium on Theory of Computing …, 2016
612016
A private and computationally-efficient estimator for unbounded gaussians
G Kamath, A Mouzakis, V Singhal, T Steinke, J Ullman
Conference on Learning Theory, 544-572, 2022
522022
New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma
G Kamath, A Mouzakis, V Singhal
Advances in Neural Information Processing Systems 35, 24405-24418, 2022
422022
Private Estimation with Public Data
A Bie, G Kamath, V Singhal
Advances in Neural Information Processing Systems 35, 18653-18666, 2022
372022
Privately learning subspaces
V Singhal, T Steinke
Advances in neural information processing systems 34, 1312-1324, 2021
262021
Private distribution learning with public data: The view from sample compression
S Ben-David, A Bie, CL Canonne, G Kamath, V Singhal
Advances in Neural Information Processing Systems 36, 7184-7215, 2023
152023
A bias-variance-privacy trilemma for statistical estimation
G Kamath, A Mouzakis, M Regehr, V Singhal, T Steinke, J Ullman
arXiv preprint arXiv:2301.13334, 2023
142023
A Polynomial Time, Pure Differentially Private Estimator for Binary Product Distributions
V Singhal
Proceedings of The 35th International Conference on Algorithmic Learning …, 2024
82024
Not all learnable distribution classes are privately learnable
M Bun, G Kamath, A Mouzakis, V Singhal
International Conference on Algorithmic Learning Theory, 390-401, 2024
22024
Private Means and the Curious Incident of the Free Lunch
J Fitzsimons, J Honaker, M Shoemate, V Singhal
arXiv preprint arXiv:2408.10438, 2024
12024
Differentially Private Statistical Estimation
V Singhal
Northeastern University, 2021
2021
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Articles 1–14