One of the most widely used techniques for data clustering is agglomerative clustering. Such algorithms have been long used across many different fields ranging from computational...
Spectral clustering algorithms have been shown to be more effective in finding clusters than some traditional algorithms such as k-means. However, spectral clustering suffers fro...
We present an estimation-theoretic approach to curve evolution for the Mumford-Shah problem. By viewing an active contour as the set of discontinuities in the Mumford-Shah problem...
Abstract. We describe the use of non-parametric permutation tests to detect activation in cortically-constrained maps of current density computed from MEG data. The methods are app...
Dimitrios Pantazis, Thomas E. Nichols, Sylvain Bai...
In lots of natural language processing tasks, the classes to be dealt with often occur heavily imbalanced in the underlying data set and classifiers trained on such skewed data t...