In this paper, we describe a nonlinear image representation based on divisive normalization that is designed to match the statistical properties of photographic images, as well as...
The ability to identify and present the most essential aspects of time-varying data is critically important in many areas of science and engineering. This paper introduces an impor...
We introduce a new inference algorithm for Dirichlet process mixture models. While Gibbs sampling and variational methods focus on local moves, the new algorithm makes more global...
In this paper, we address the problem of finding the pre-image of a feature vector in the feature space induced by a kernel. This is of central importance in some kernel applicatio...
In this paper we present a clustered, multiple-clock domain (CMCD) microarchitecture that combines the benefits of both clustering and Globally Asynchronous Locally Synchronous (G...