5 citations · 8 across the 5 of their papers we have counts for
5 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…
Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time
Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff +1
We study fundamental problems in linear algebra, such as finding a maximal linearly independent subset of rows or columns (a basis), solving linear regression, or computing a subsp…
Learning-Augmented Algorithms for Online Linear and Semidefinite Programming
Elena Grigorescu, Young-San Lin, Sandeep Silwal +2
Semidefinite programming (SDP) is a unifying framework that generalizes both linear programming and quadratically-constrained quadratic programming, while also yielding efficient s…
Hardness and Algorithms for Robust and Sparse Optimization
Eric Price, Sandeep Silwal, Samson Zhou
We explore algorithms and limitations for sparse optimization problems such as sparse linear regression and robust linear regression. The goal of the sparse linear regression probl…
Dimensionality Reduction for Wasserstein Barycenter
Zachary Izzo, Sandeep Silwal, Samson Zhou
The Wasserstein barycenter is a geometric construct which captures the notion of centrality among probability distributions, and which has found many applications in machine learni…