For supervised and unsupervised learning, positive definite kernels allow to use large and potentially infinite dimensional feature spaces with a computational cost that only depe...
Abstract--This paper describes an interactive tool for constrained clustering that helps users to select effective constraints efficiently during the constrained clustering process...
We present a method to automatically learn object categories from unlabeled images. Each image is represented by an unordered set of local features, and all sets are embedded into...
Document clustering is a very hard task in Automatic Text Processing since it requires to extract regular patterns from a document collection without a priori knowledge on the cat...
We propose a multi-document generic summarization model based on the budgeted median problem. Our model selects sentences to generate a summary so that every sentence in the docum...