Learning Bayesian Belief Networks (BBN) from corpora and incorporating the extracted inferring knowledge with a Support Vector Machines (SVM) classifier has been applied to charac...
This paper treats tracking as a foreground/background classification problem and proposes an online semisupervised learning framework. Initialized with a small number of labeled ...
We present a vision based, adaptive, decision theoretic model of human facial displays in interactions. The model is a partially observable Markov decision process, or POMDP. A POM...
From a conceptual point of view, belief revision and learning are quite similar. Both methods change the belief state of an intelligent agent by processing incoming information. Ho...
Thomas Leopold, Gabriele Kern-Isberner, Gabriele P...
We study the problem of learning to rank images for image retrieval. For a noisy set of images indexed or tagged by the same keyword, we learn a ranking model from some training e...