93 citations · 426 across the 43 of their papers we have counts for
6 papers · 1 filter
Hutch++: Optimal Stochastic Trace Estimation
Raphael A. Meyer, Cameron Musco, Christopher Musco +1
We study the problem of estimating the trace of a matrix that can only be accessed through matrix-vector multiplication. We introduce a new randomized algorithm, Hutch++, which…
Fast and Near-Optimal Diagonal Preconditioning
Arun Jambulapati, Jerry Li, Christopher Musco +2
The convergence rates of iterative methods for solving a linear system typically depend on the condition number of the matrix . Preconditioning is a…
The Statistical Cost of Robust Kernel Hyperparameter Tuning
Raphael A. Meyer, Christopher Musco
This paper studies the statistical complexity of kernel hyperparameter tuning in the setting of active regression under adversarial noise. We consider the problem of finding the be…
Graph Learning for Inverse Landscape Genetics
Prathamesh Dharangutte, Christopher Musco
The problem of inferring unknown graph edges from numerical data at a graph's nodes appears in many forms across machine learning. We study a version of this problem that arises in…
Fourier Sparse Leverage Scores and Approximate Kernel Learning
Tamás Erdélyi, Cameron Musco, Christopher Musco
We prove new explicit upper bounds on the leverage scores of Fourier sparse functions under both the Gaussian and Laplace measures. In particular, we study -sparse functions of…
Projection-Cost-Preserving Sketches: Proof Strategies and Constructions
Cameron Musco, Christopher Musco
In this note we illustrate how common matrix approximation methods, such as random projection and random sampling, yield projection-cost-preserving sketches, as introduced in [FSS1…