This paper introduces a new discriminative learning technique for link prediction based on the matrix alignment approach. Our algorithm automatically determines the most predictiv...
Jerry Scripps, Pang-Ning Tan, Feilong Chen, Abdol-...
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...
Recent work shows how to use local spatio-temporal features to learn models of realistic human actions from video. However, existing methods typically rely on a predefined spatial...
We present a framework for learning features for visual discrimination. The learning system is exposed to a sequence of training images. Whenever it fails to recognize a visual co...
Bottom-up cortical representations of visual conspicuity interact with top-down internal cognitive models of the external world to control eye movements, EMs, and the closely linke...
Claudio M. Privitera, Orazio Gallo, Giorgio Grimol...