We address the problem of learning distance metrics using side-information in the form of groups of "similar" points. We propose to use the RCA algorithm, which is a sim...
Concentration inequalities that incorporate variance information (such as Bernstein's or Bennett's inequality) are often significantly tighter than counterparts (such as...
Stewart's Krylov-Schur algorithm offers two advantages over Sorensen's implicitly restarted Arnoldi (IRA) algorithm. The first is ease of deflation of converged Ritz vect...
Feature and structure selection is an important part of many classification problems. In previous papers, an approach called basis pursuit classification has been proposed which p...
The maximization of a full-rank quadratic form over a finite alphabet is NP-hard in both a worst-case sense and an average sense. Interestingly, if the rank of the form is not a ...