3 citations · 6 across the 21 of their papers we have counts for
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Clustering Mixtures of Bounded Covariance Distributions Under Optimal Separation
Ilias Diakonikolas, Daniel M. Kane, Jasper C. H. Lee +1
We study the clustering problem for mixtures of bounded covariance distributions, under a fine-grained separation assumption. Specifically, given samples from a -component mixtu…
Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean Estimation and Linear Regression
Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia +1
We study the fundamental problems of Gaussian mean estimation and linear regression with Gaussian covariates in the presence of Huber contamination. Our main contribution is the de…
SQ Lower Bounds for Learning Bounded Covariance GMMs
Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas +1
We study the complexity of learning mixtures of separated Gaussians with common unknown bounded covariance matrix. Specifically, we focus on learning Gaussian mixture models (GMMs)…
Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA
Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia +1
We study principal component analysis (PCA), where given a dataset in from a distribution, the task is to find a unit vector that approximately maximizes the var…
A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm
Ilias Diakonikolas, Daniel M. Kane, Jasper C. H. Lee +2
We study the problem of list-decodable Gaussian covariance estimation. Given a multiset of points in such that an unknown fraction of points in ar…