Algorithms for Heavy-Tailed Statistics: Regression, Covariance Estimation, and Beyond

Cherapanamjeri Yeshwanth
Cherapanamjeri Yeshwanth
Kathuria Tarun
Kathuria Tarun
Tripuraneni Nilesh
Tripuraneni Nilesh

STOC '20: 52nd Annual ACM SIGACT Symposium on Theory of Computing Chicago IL USA June, 2020, pp. 601-609, 2019.

Cited by: 11|Views20
EI

Abstract:

We study polynomial-time algorithms for linear regression and covariance estimation in the absence of strong (Gaussian) assumptions on the underlying distributions of samples, making assumptions instead about only finitely-many moments. We focus on how many samples are required to perform estimation and regression with high accuracy and e...More

Code:

Data:

Your rating :
0

 

Tags
Comments