This paper is concerned with classifying high dimensional data into one of two categories. In various settings, such as when dealing with fMRI and microarray data, the number of v...
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 ...
Humans tend to group together related properties in order to understand complex phenomena. When modeling large problems with limited representational resources, it is important to...
Background: Several supervised and unsupervised learning tools are available to classify functional genomics data. However, relatively less attention has been given to exploratory...
We derive PAC-Bayesian generalization bounds for supervised and unsupervised learning models based on clustering, such as co-clustering, matrix tri-factorization, graphical models...