Christopher Musco

Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition

2015 · arXiv (Cornell University)

Since being analyzed by Rokhlin, Szlam, and Tygert and popularized by Halko, Martinsson, and Tropp, randomized Simultaneous Power Iteration has become the method of choice for approximate singular value decomposition. It is more accurate than …

Stronger and Faster Approximate Singular Value Decomposition via the Block Lanczos Method

2015 · arXiv (Cornell University)

Since being analyzed by Rokhlin, Szlam, and Tygert and popularized by Halko, Martinsson, and Tropp, randomized Simultaneous Power Iteration has become the method of choice for approximate singular value decomposition. It is more accurate than …

Query Efficient Structured Matrix Learning

2025 · arXiv (Cornell University)

We study the problem of learning a structured approximation (low-rank, sparse, banded, etc.) to an unknown matrix $A$ given access to matrix-vector product (matvec) queries of the form $x \rightarrow Ax$ and $x \rightarrow A^Tx$. …