27 citations · 61 across the 27 of their papers we have counts for
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SoS Certificates for Sparse Singular Values and Their Applications: Robust Statistics, Subspace Distortion, and More
Ilias Diakonikolas, Samuel B. Hopkins, Ankit Pensia +1
We study for random rectangular matrices. If is an matrix with independent Gaussian entries, we give a new family of…
SoS Certifiability of Subgaussian Distributions and its Algorithmic Applications
Ilias Diakonikolas, Samuel B. Hopkins, Ankit Pensia +1
We prove that there is a universal constant so that for every , every centered subgaussian distribution on , and every even $p \in…
Optimal Robust Estimation under Local and Global Corruptions: Stronger Adversary and Smaller Error
Thanasis Pittas, Ankit Pensia
Algorithmic robust statistics has traditionally focused on the contamination model where a small fraction of the samples are arbitrarily corrupted. We consider a recent contaminati…
Robust Sparse Estimation for Gaussians with Optimal Error under Huber Contamination
Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar +2
We study Gaussian sparse estimation tasks in Huber's contamination model with a focus on mean estimation, PCA, and linear regression. For each of these tasks, we give the first sam…
A Sub-Quadratic Time Algorithm for Robust Sparse Mean Estimation
Ankit Pensia
We study the algorithmic problem of sparse mean estimation in the presence of adversarial outliers. Specifically, the algorithm observes a \emph{corrupted} set of samples from $\ma…
The Sample Complexity of Simple Binary Hypothesis Testing
Ankit Pensia, Varun Jog, Po-Ling Loh
The sample complexity of simple binary hypothesis testing is the smallest number of i.i.d.\ samples required to distinguish between two distributions and in either: (i) the…
Black-Box -to--PCA Reductions: Theory and Applications
Arun Jambulapati, Syamantak Kumar, Jerry Li +3
The -principal component analysis (-PCA) problem is a fundamental algorithmic primitive that is widely-used in data analysis and dimensionality reduction applications. In sta…