6 citations · 9 across the 10 of their papers we have counts for
10 papers
How to Protect Copyright Data in Optimization of Large Language Models?
Timothy Chu, Zhao Song, Chiwun Yang
Large language models (LLMs) and generative AI have played a transformative role in computer research and applications. Controversy has arisen as to whether these models output cop…
Spectral Clustering on Large Datasets: When Does it Work? Theory from Continuous Clustering and Density Cheeger-Buser
Timothy Chu, Gary Miller, Noel Walkington
Spectral clustering is one of the most popular clustering algorithms that has stood the test of time. It is simple to describe, can be implemented using standard linear algebra, an…
Algorithms and Hardness for Linear Algebra on Geometric Graphs
Josh Alman, Timothy Chu, Aaron Schild +1
For a function , and a set of points, the $\mathsf{K…
Metric Transforms and Low Rank Matrices via Representation Theory of the Real Hyperrectangle
Josh Alman, Timothy Chu, Gary Miller +3
In this paper, we develop a new technique which we call representation theory of the real hyperrectangle, which describes how to compute the eigenvectors and eigenvalues of certain…
Weighted Cheeger and Buser Inequalities, with Applications to Clustering and Cutting Probability Densities
Timothy Chu, Gary L. Miller, Noel J. Walkington +1
In this paper, we show how sparse or isoperimetric cuts of a probability density function relate to Cheeger cuts of its principal eigenfunction, for appropriate definitions of `spa…
Constant Arboricity Spectral Sparsifiers
Timothy Chu, Michael B. Cohen, Jakub W. Pachocki +1
We show that every graph is spectrally similar to the union of a constant number of forests. Moreover, we show that Spielman-Srivastava sparsifiers are the union of O(logn) forests…