We present a new algorithm that reduces the space complexity of heuristic search. It is most effective for problem spaces that grow polynomially with problem size, but contain lar...
Similarity search is a fundamental operation for applications that deal with unstructured data sources. In this paper we propose a new pivot-based method for similarity search, ca...
This paper presents a novel method for reducing the dimensionality of kernel spaces. Recently, to maintain the convexity of training, loglinear models without mixtures have been u...
We face the question of how to produce a scale space of image intensities relative to a scale space of objects or other characteristic image regions filling up the image space, whe...
Stephen M. Pizer, Ja-Yeon Jeong, Robert E. Broadhu...
Many linear discriminant analysis (LDA) and kernel Fisher discriminant analysis (KFD) methods are based on the restrictive assumption that the data are homoscedastic. In this paper...