We design a randomized polynomial time algorithm which, given a 3-tensor of real numbers A = {aijk}n i,j,k=1 such that for all i, j, k ∈ {1, . . . , n} we have ai jk = aik j = a...
We introduce a boosting framework to solve a classification problem with added manifold and ambient regularization costs. It allows for a natural extension of boosting into both s...
Nicolas Loeff, David A. Forsyth, Deepak Ramachandr...
Abstract We develop a distance metric for clustering and classification algorithms which is invariant to affine transformations and includes priors on the transformation parameters...
In this paper we investigate the use of data driven clustering methods for functional connectivity analysis in fMRI. In particular, we consider the K-Means and Spectral Clustering...
Archana Venkataraman, Koene R. A. Van Dijk, Randy ...
Clustering has been one of the most widely studied topics in data mining and k-means clustering has been one of the popular clustering algorithms. K-means requires several passes ...