We propose a family of clustering algorithms based on the maximization of dependence between the input variables and their cluster labels, as expressed by the Hilbert-Schmidt Inde...
Le Song, Alexander J. Smola, Arthur Gretton, Karst...
Applications such as parallel computing, online games, and content distribution networks need to run on a set of resources with particular network connection characteristics to ge...
In this paper, we describe an approach for the automatic medical image annotation task of the 2009 CLEF cross-language image retrieval campaign (ImageCLEF). This work is focused o...
We present a novel, maximum likelihood framework for automatic spike-sorting based on a joint statistical model of action potential waveform shape and inter-spike interval duratio...
Feature space clustering is a popular approach to image segmentation, in which a feature vector of local properties (such as intensity, texture or motion) is computed at each pixe...