Abstract. In this paper, we present a novel method for reducing the computational complexity of a Support Vector Machine (SVM) classifier without significant loss of accuracy. We a...
Abstract. The Support Kernel Machine (SKM) and the Relevance Kernel Machine (RKM) are two principles for selectively combining objectrepresentation modalities of different kinds b...
Alexander Tatarchuk, Eugene Urlov, Vadim Mottl, Da...
Abstract. Proof-carrying code and other applications in computer security require machine-checkable proofs of properties of machine-language programs. These in turn require axioms ...
Abstract. Markov Random Fields (MRFs) are a popular and wellmotivated model for many medical image processing tasks such as segmentation. Discriminative Random Fields (DRFs), a dis...
Chi-Hoon Lee, Mark Schmidt, Albert Murtha, Aalo Bi...
Abstract— A distributed online learning framework for support vector machines (SVMs) is presented and analyzed. First, the generic binary classification problem is decomposed in...