We address the problem of the segmentation of cerebral white matter structures from diffusion tensor images. Our approach is grounded on the theoretically well-founded differential...
This paper investigates a new learning formulation called structured sparsity, which is a naturalextensionofthestandardsparsityconceptinstatisticallearningandcompressivesensing. B...
Dual supervision refers to the general setting of learning from both labeled examples as well as labeled features. Labeled features are naturally available in tasks such as text c...
Vikas Sindhwani, Prem Melville, Richard D. Lawrenc...
We consider the problem of learning density mixture models for classification. Traditional learning of mixtures for density estimation focuses on models that correctly represent t...
We study the problem of discovering a manifold that best preserves information relevant to a nonlinear regression. Solving this problem involves extending and uniting two threads ...