13 citations · 26 across the 9 of their papers we have counts for
7 papers
Kernel Interpolation with Sparse Grids
Mohit Yadav, Daniel Sheldon, Cameron Musco
Structured kernel interpolation (SKI) accelerates Gaussian process (GP) inference by interpolating the kernel covariance function using a dense grid of inducing points, whose corre…
Optimal Sketching Bounds for Sparse Linear Regression
Tung Mai, Alexander Munteanu, Cameron Musco +3
We study oblivious sketching for -sparse linear regression under various loss functions such as an norm, or from a broad class of hinge-like loss functions, which inclu…
No-regret Algorithms for Fair Resource Allocation
Abhishek Sinha, Ativ Joshi, Rajarshi Bhattacharjee +2
We consider a fair resource allocation problem in the no-regret setting against an unrestricted adversary. The objective is to allocate resources equitably among several agents in…
Sublinear Time Approximation of Text Similarity Matrices
Archan Ray, Nicholas Monath, Andrew McCallum +1
We study algorithms for approximating pairwise similarity matrices that arise in natural language processing. Generally, computing a similarity matrix for data points requires…
Computational Tradeoffs in Biological Neural Networks: Self-Stabilizing Winner-Take-All Networks
Nancy Lynch, Cameron Musco, Merav Parter
We initiate a line of investigation into biological neural networks from an algorithmic perspective. We develop a simplified but biologically plausible model for distributed comput…
Dimensionality Reduction for k-Means Clustering and Low Rank Approximation
Michael B. Cohen, Sam Elder, Cameron Musco +2
We show how to approximate a data matrix with a much smaller sketch that can be used to solve a general class of constrained k-rank approximation p…