1 citations · 1 across the 2 of their papers we have counts for
8 papers
Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation
Ainesh Bakshi, Piotr Indyk, Praneeth Kacham +2
Kernel matrices, as well as weighted graphs represented by them, are ubiquitous objects in machine learning, statistics and other related fields. The main drawback of using kernel…
Learning a Latent Simplex in Input-Sparsity Time
Ainesh Bakshi, Chiranjib Bhattacharyya, Ravi Kannan +2
We consider the problem of learning a latent -vertex simplex , given access to , which can be viewed as a data matrix with …
Robust Linear Regression: Optimal Rates in Polynomial Time
Ainesh Bakshi, Adarsh Prasad
We obtain robust and computationally efficient estimators for learning several linear models that achieve statistically optimal convergence rate under minimal distributional assump…
Testing Positive Semi-Definiteness via Random Submatrices
Ainesh Bakshi, Nadiia Chepurko, Rajesh Jayaram
We study the problem of testing whether a matrix with bounded entries () is positive semi-definite (PSD), or…
Outlier-Robust Clustering of Non-Spherical Mixtures
Ainesh Bakshi, Pravesh Kothari
We give the first outlier-robust efficient algorithm for clustering a mixture of statistically separated d-dimensional Gaussians (k-GMMs). Concretely, our algorithm takes input…
List-Decodable Subspace Recovery: Dimension Independent Error in Polynomial Time
Ainesh Bakshi, Pravesh K. Kothari
In list-decodable subspace recovery, the input is a collection of points (for some ) of which are drawn i.i.d. from a distribution with a isotropic…