In this paper we describe a new method to reduce the complexity of support vector machines by reducing the number of necessary support vectors included in their solutions. The red...
Many unsupervised algorithms for nonlinear dimensionality reduction, such as locally linear embedding (LLE) and Laplacian eigenmaps, are derived from the spectral decompositions o...
The proliferation of text documents on the web as well as within institutions necessitates their convenient organization to enable efficient retrieval of information. Although tex...
Sriharsha Veeramachaneni, Diego Sona, Paolo Avesan...
We study the problem of modeling species geographic distributions, a critical problem in conservation biology. We propose the use of maximum-entropy techniques for this problem, s...
We examine the set covering machine when it uses data-dependent half-spaces for its set of features and bound its generalization error in terms of the number of training errors an...
Mario Marchand, Mohak Shah, John Shawe-Taylor, Mar...