Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
We introduce confidence-weighted linear classifiers, which add parameter confidence information to linear classifiers. Online learners in this setting update both classifier param...
A logistic regression classification algorithm is developed for problems in which the feature vectors may be missing data (features). Single or multiple imputation for the missing...
David Williams, Xuejun Liao, Ya Xue, Lawrence Cari...
In this paper the development of an intelligent image content-based search engine for the World Wide Web is presented. Information Web Crawlers continuously traverse the Internet ...
Ioannis Kompatsiaris, Evangelia Triantafyllou, Mic...
Video codecs that use motion compensation have recently achieved performance improvements from the use of intra/inter mode switching decisions within a ratedistortion framework. A...