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Samuel B. Hopkins
Samuel B. Hopkins
Dirección de correo verificada de mit.edu - Página principal
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A nearly tight sum-of-squares lower bound for the planted clique problem
B Barak, S Hopkins, J Kelner, PK Kothari, A Moitra, A Potechin
SIAM Journal on Computing 48 (2), 687-735, 2019
2522019
Mixture models, robustness, and sum of squares proofs
SB Hopkins, J Li
Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing …, 2018
1762018
Tensor principal component analysis via sum-of-squares proofs
SB Hopkins, J Shi, D Steurer
arXiv preprint arXiv:1507.03269, 2015
1712015
Fast spectral algorithms from sum-of-squares proofs: tensor decomposition and planted sparse vectors
SB Hopkins, T Schramm, J Shi, D Steurer
arXiv preprint arXiv:1512.02337, 2016
1522016
The power of sum-of-squares for detecting hidden structures
SB Hopkins, PK Kothari, A Potechin, P Raghavendra, T Schramm, ...
2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS …, 2017
1422017
Bayesian estimation from few samples: community detection and related problems
SB Hopkins, D Steurer
arXiv preprint arXiv:1710.00264, 2017
137*2017
Sub-gaussian mean estimation in polynomial time
SB Hopkins
arXiv preprint arXiv:1809.07425 120, 2018
115*2018
Quantum entropy scoring for fast robust mean estimation and improved outlier detection
Y Dong, S Hopkins, J Li
Advances in Neural Information Processing Systems 32, 2019
1032019
Statistical inference and the sum of squares method
S Hopkins
Cornell University, 2018
1012018
On the integrality gap of degree-4 sum of squares for planted clique
SB Hopkins, P Kothari, AH Potechin, P Raghavendra, T Schramm
ACM Transactions on Algorithms (TALG) 14 (3), 1-31, 2018
67*2018
Robustly learning any clusterable mixture of gaussians
I Diakonikolas, SB Hopkins, D Kane, S Karmalkar
arXiv preprint arXiv:2005.06417, 2020
65*2020
Statistical query algorithms and low-degree tests are almost equivalent
M Brennan, G Bresler, SB Hopkins, J Li, T Schramm
arXiv preprint arXiv:2009.06107, 2020
632020
Robust and heavy-tailed mean estimation made simple, via regret minimization
S Hopkins, J Li, F Zhang
Advances in Neural Information Processing Systems 33, 11902-11912, 2020
622020
Efficient mean estimation with pure differential privacy via a sum-of-squares exponential mechanism
SB Hopkins, G Kamath, M Majid
Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing …, 2022
482022
Algorithms for heavy-tailed statistics: Regression, covariance estimation, and beyond
Y Cherapanamjeri, SB Hopkins, T Kathuria, P Raghavendra, ...
Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing …, 2020
422020
How hard is robust mean estimation?
SB Hopkins, J Li
Conference on learning theory, 1649-1682, 2019
322019
Robustness implies privacy in statistical estimation
SB Hopkins, G Kamath, M Majid, S Narayanan
Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 497-506, 2023
312023
The Franz-Parisi criterion and computational trade-offs in high dimensional statistics
AS Bandeira, A El Alaoui, S Hopkins, T Schramm, AS Wein, I Zadik
Advances in Neural Information Processing Systems 35, 33831-33844, 2022
272022
A robust spectral algorithm for overcomplete tensor decomposition
SB Hopkins, T Schramm, J Shi
Conference on Learning Theory, 1683-1722, 2019
252019
Sum-of-squares meets program obfuscation, revisited
B Barak, SB Hopkins, A Jain, P Kothari, A Sahai
Advances in Cryptology–EUROCRYPT 2019: 38th Annual International Conference …, 2019
202019
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