The problem of obtaining the maximum a posteriori (map) estimate of a discrete random field is of fundamental importance in many areas of Computer Science. In this work, we build ...
Recently, a very appealing approach was proposed to compute the entire solution path for support vector classification (SVC) with very low extra computational cost. This approach ...
Given a classification problem, our goal is to find a low-dimensional linear transformation of the feature vectors which retains information needed to predict the class labels. We...
We propose a fast iterative classification algorithm for Kernel Fisher Discriminant (KFD) using heterogeneous kernel models. In contrast with the standard KFD that requires the us...
Most clustering algorithms in fMRI analysis implicitly require some nontrivial assumption on data structure. Due to arbitrary distribution of fMRI time series in the temporal doma...