Multiple-instance learning (MIL) is a generalization of the supervised learning problem where each training observation is a labeled bag of unlabeled instances. Several supervised ...
Biological research is currently undergoing a revolution. With the advent of microarray technology the behavior of thousands of genes can be measured simultaneously. This capabilit...
Herman Midelfart, Henryk Jan Komorowski, Kristin N...
The problem of overlapping clustering, where a point is allowed to belong to multiple clusters, is becoming increasingly important in a variety of applications. In this paper, we ...
In this paper, we propose a novel classification method, called local manifold matching (LMM), for face recognition. LMM has great representational capacity of available prototypes...
Based on simple methods such as observing word and part of speech tag co-occurrence and clustering, we generate syntactic parses of sentences in an entirely unsupervised and self-...