Data Representation and Compression Using Linear-Programming Approximations

no code implementations • 20 Nov 2015 • Hristo S. Paskov, John C. Mitchell, Trevor J. Hastie

We also discuss how to derive features from the compressed documents and show that while certain unregularized linear models are invariant to the structure of the compressed dictionary, this structure may be used to regularize learning.

feature selection

Compressive Feature Learning

no code implementations • NeurIPS 2013 • Hristo S. Paskov, Robert West, John C. Mitchell, Trevor Hastie

This paper addresses the problem of unsupervised feature learning for text data.

Dimensionality Reduction Text Categorization