Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a linear combination of the input variables while constraining the number of nonze...
Alexandre d'Aspremont, Francis R. Bach, Laurent El...
In this paper, a new theoretical framework based on hidden Markov model (HMM) and independent component analysis (ICA) mixture model is presented for content analysis of video, nam...
Conditional Random Fields (CRFs; Lafferty, McCallum, & Pereira, 2001) provide a flexible and powerful model for learning to assign labels to elements of sequences in such appl...
Thomas G. Dietterich, Adam Ashenfelter, Yaroslav B...
A powerful approach to search is to try to learn a distribution of good solutions (in particular of the dependencies between their variables) and use this distribution as a basis ...
We address the e-rulemaking problem of reducing the manual labor required to analyze public comment sets. In current and previous work, for example, text categorization techniques...