93 citations · 426 across the 43 of their papers we have counts for
5 papers · 1 filter
Near-Linear Sample Complexity for Polynomial Regression
Raphael A. Meyer, Cameron Musco, Christopher Musco +2
We study polynomial regression. Given query access to a function , the goal is to find a degree polynomial such that, for a giv…
Active Learning for Single Neuron Models with Lipschitz Non-Linearities
Aarshvi Gajjar, Chinmay Hegde, Christopher Musco
We consider the problem of active learning for single neuron models, also sometimes called ``ridge functions'', in the agnostic setting (under adversarial label noise). Such models…
A Tight Analysis of Hutchinson's Diagonal Estimator
Prathamesh Dharangutte, Christopher Musco
Let be a matrix with diagonal and let be with its diagonal set to all zeros. We sho…
Fast Regression for Structured Inputs
Raphael A. Meyer, Cameron Musco, Christopher Musco +2
We study the regression problem, which requires finding that minimizes for a matrix $\mathbf{A}\in\mat…
Low-memory Krylov subspace methods for optimal rational matrix function approximation
Tyler Chen, Anne Greenbaum, Cameron Musco +1
We describe a Lanczos-based algorithm for approximating the product of a rational matrix function with a vector. This algorithm, which we call the Lanczos method for optimal ration…