Abstract An extension of the Gauss-Newton algorithm is proposed to find local minimizers of penalized nonlinear least squares problems, under generalized Lipschitz assumptions. Co...
We present a principled methodology for filtering news stories by formal measures of information novelty, and show how the techniques can be used to custom-tailor newsfeeds based ...
Evgeniy Gabrilovich, Susan T. Dumais, Eric Horvitz
Mixture models form one of the most widely used classes of generative models for describing structured and clustered data. In this paper we develop a new approach for the analysis...
Abstract. Sreedhar et al. [SGL98, Sre95] have presented an eliminationbased algorithm to solve data flow problems. A thorough analysis of the algorithm shows that the worst-case pe...
In this article, a novel concept is introduced by using both unsupervised and supervised learning. For unsupervised learning, the problem of fuzzy clustering in microarray data as ...