The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
Background: Feature selection is an important pre-processing task in the analysis of complex data. Selecting an appropriate subset of features can improve classification or cluste...
Assaf Gottlieb, Roy Varshavsky, Michal Linial, Dav...
Independence analysis is the problem of determining whether an update affects the result of a query, e.g. a constraint or materialized view. We develop a new, modular framework fo...
Background: The number of available genome sequences is increasing, and easy-to-use software that enables efficient comparative analysis is needed. Results: We developed GenomeMat...
Abstract--This paper presents a technique inspired by the negative selection mechanism of the immune system that can detect foreign patterns in the complement (nonself) space. In p...