This paper presents a novel approach for online subspace learning based on an incremental version of the nonparametric discriminant analysis (NDA). For many real-world applications...
Recently, there has been an increased interest in "lifelong" machine learning methods, that transfer knowledge across multiple learning tasks. Such methods have repeated...
Many applications in information retrieval, natural language processing, data mining, and related fields require a ranking of instances with respect to a specified criteria as op...
Abstract. We propose a framework that learns functional objectes from spatio-temporal data sets such as those abstracted from video. The data is represented as one activity graph t...
Muralikrishna Sridhar, Anthony G. Cohn, David C. H...
Abstract. We consider the problem of training discriminative structured output predictors, such as conditional random fields (CRFs) and structured support vector machines (SSVMs)....
Patrick Pletscher, Cheng Soon Ong, Joachim M. Buhm...