39 citations · 124 across the 17 of their papers we have counts for
4 papers · 1 filter
Sparse sketches with small inversion bias
Michał Dereziński, Zhenyu Liao, Edgar Dobriban +1
For a tall matrix and a random sketching matrix , the sketched estimate of the inverse covariance matrix is typically biased: $E[(\…
Sparse Quantized Spectral Clustering
Zhenyu Liao, Romain Couillet, Michael W. Mahoney
Given a large data matrix, sparsifying, quantizing, and/or performing other entry-wise nonlinear operations can have numerous benefits, ranging from speeding up iterative algorithm…
Kernel regression in high dimensions: Refined analysis beyond double descent
Fanghui Liu, Zhenyu Liao, Johan A. K. Suykens
In this paper, we provide a precise characterization of generalization properties of high dimensional kernel ridge regression across the under- and over-parameterized regimes, depe…
A Random Matrix Analysis of Random Fourier Features: Beyond the Gaussian Kernel, a Precise Phase Transition, and the Corresponding Double Descent
Zhenyu Liao, Romain Couillet, Michael W. Mahoney
This article characterizes the exact asymptotics of random Fourier feature (RFF) regression, in the realistic setting where the number of data samples , their dimension , and…