We consider feature selection for text classification both theoretically and empirically. Our
main result is an unsupervised feature selection strategy for which we give worst-case …

The $\ell_p$ regression problem takes as input a matrix $A\in\mathbb{R}^{n\times d}$, a
vector $b\in\mathbb{R}^n$, and a number $p\in[1,\infty)$, and it returns as output a number ${\…

We started investigating the collection of HTML tables on the Web and developed the
WebTables system a few years ago [4]. Since then, our work has been motivated by applying …

We consider the wavelet synopsis construction problem for data streams where given n
numbers we wish to estimate the data by constructing a synopsis, whose size, say B is much …

A central problem in approximation theory is the concise representation of functions. Given a
function or signal described as a vector in high-dimensional space, the goal is to represent …

This paper addresses the problem of finding a B -term wavelet representation of a given
discrete function fepsiR n whose distance from is minimized. The problem is well understood …

Isotonic regression, the problem of finding values that best fit given observations and conform
to specific ordering constraints, has found many applications in biomedical research and …

The paper presents an empirical exploration of google.com query stream language modeling.
We describe the normalization of the typed query stream resulting in out-of-vocabulary (…

We consider the problem of fitting an n× n distance matrix M by a tree metric T. We give a
factor O( min {n 1/p ,(klogn) 1/p }) approximation algorithm for finding the closest ultrametric T …

With the availability of large amounts of training data relevant to speech recognition scenarios,
scalability becomes a very productive way to improve language model performance. We …