2 citations · 4 across the 4 of their papers we have counts for
5 papers · 1 filter
Approximate Guarantees for Dictionary Learning
Aditya Bhaskara, Wai Ming Tai
In the dictionary learning (or sparse coding) problem, we are given a collection of signals (vectors in ), and the goal is to find a "basis" in which the signals have…
Learning In Practice: Reasoning About Quantization
Annie Cherkaev, Waiming Tai, Jeff Phillips +1
There is a mismatch between the standard theoretical analyses of statistical machine learning and how learning is used in practice. The foundational assumption supporting the theor…
The GaussianSketch for Almost Relative Error Kernel Distance
Jeff M. Phillips, Wai Ming Tai
We introduce two versions of a new sketch for approximately embedding the Gaussian kernel into Euclidean inner product space. These work by truncating infinite expansions of the Ga…
Near-Optimal Coresets of Kernel Density Estimates
Jeff M. Phillips, Wai Ming Tai
We construct near-optimal coresets for kernel density estimates for points in when the kernel is positive definite. Specifically we show a polynomial time constructi…
Improved Coresets for Kernel Density Estimates
Jeff M. Phillips, Wai Ming Tai
We study the construction of coresets for kernel density estimates. That is we show how to approximate the kernel density estimate described by a large point set with another kerne…