activity
20182022
most citedStatistical Query Lower Bounds for List-Decodable Linear Regression

1 citations · 2 across the 5 of their papers we have counts for

collaborators

8 papers

cs.DS2022

Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions

Ilias Diakonikolas, Daniel M. Kane, Jasper C. H. Lee +1

We study the fundamental task of outlier-robust mean estimation for heavy-tailed distributions in the presence of sparsity. Specifically, given a small number of corrupted samples…

math.ST20221 cited

Gaussian Mean Testing Made Simple

Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia

We study the following fundamental hypothesis testing problem, which we term Gaussian mean testing. Given i.i.d. samples from a distribution on , the task is to d…

math.ST2021

Sharp Concentration Inequalities for the Centered Relative Entropy

Alankrita Bhatt, Ankit Pensia

We study the relative entropy between the empirical estimate of a discrete distribution and the true underlying distribution. If the minimum value of the probability mass function…

cs.DS20211 cited

Statistical Query Lower Bounds for List-Decodable Linear Regression

Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia +2

We study the problem of list-decodable linear regression, where an adversary can corrupt a majority of the examples. Specifically, we are given a set of labeled examples $(x, y…

math.ST2020

Outlier Robust Mean Estimation with Subgaussian Rates via Stability

Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia

We study the problem of outlier robust high-dimensional mean estimation under a finite covariance assumption, and more broadly under finite low-degree moment assumptions. We consid…

cs.LG2020

Optimal Lottery Tickets via SubsetSum: Logarithmic Over-Parameterization is Sufficient

Ankit Pensia, Shashank Rajput, Alliot Nagle +2

The strong {\it lottery ticket hypothesis} (LTH) postulates that one can approximate any target neural network by only pruning the weights of a sufficiently over-parameterized rand…