We propose a novel scheme for using supervised learning for function-based classification of objects in 3D images. During the learning process, a generic multi-level hierarchical ...
This paper presents an efficient algorithm for learning Bayesian belief networks from databases. The algorithm takes a database as input and constructs the belief network structur...
This paper presents probabilistic modeling methods to solve the problem of discriminating between five facial orientations with very little labeled data. Three models are explored...
We define a process called congealing in which elements of a dataset (images) are brought into correspondence with each other jointly, producing a data-defined model. It is based ...
Erik G. Miller, Nicholas E. Matsakis, Paul A. Viol...
Researchers who make tutoring systems would like to know which sequences of educational content lead to the most effective learning by their students. The majority of data collecte...