We study estimation of mixture models for problems in which multiple views of the instances are available. Examples of this setting include clustering web pages or research papers ...
Understanding the structure of multidimensional patterns, especially in unsupervised case, is of fundamental importance in data mining, pattern recognition and machine learning. Se...
The importance of learning distance functions is gradually being acknowledged by the machine learning community, and different techniques are suggested that can successfully learn ...
Temporal information has been the focus of recent attention in information extraction, leading to some standardization effort, in particular for the task of relating events in a t...
A number of updates for density matrices have been developed recently that are motivated by relative entropy minimization problems. The updates involve a softmin calculation based...