Author

Rajarshi Bhattacharjee

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Preprint Aug 2026

Sublinear Time Eigenvector Approximation via Column Sampling

This work gives the first sublinear time classical algorithms for eigenvector approximation with additive error $\epsilon \|A\|_F$ and presents an alternative approach, based on a truncated Nystrom method, that achieves near optimal sample complexity for general symmetric matrices, and improved bounds for positive semi...

Rajarshi Bhattacharjee, Cameron Musco, Dominic Rutkowski · 1 citation · ⚡1

Preprint Aug 2026

Fast Length-Squared Sampling for Positive-Semidefinite Matrices

We describe a simple rejection-sampling-based algorithm to perform length-squared sampling on an $n \times n$ positive-semidefinite (psd) matrix: that is, to sample a column with probability proportional to its squared $\ell_2$-norm. The algorithm runs in just $O(n)$ expected time, which is significantly sublinear in t...

Rajarshi Bhattacharjee, Ethan N. Epperly, Cameron Musco et al. · 0 citations