In this paper we propose an approximated structured prediction framework for large scale graphical models and derive message-passing algorithms for learning their parameters effic...
One-to-one codes are "one shot" codes that assign a distinct codeword to source symbols and are not necessarily prefix codes (more generally, uniquely decodable). For ex...
Inductive representation of conditional knowledge means to complete knowledge appropriately and can be looked upon as an instance of quite a general representation problem. The cr...
This paper describes an unsupervised algorithm for segmenting categorical time series into episodes. The VOTING-EXPERTS algorithm first collects statistics about the frequency an...
This paper presents a novel theory for learning generic prior models from a set of observed natural images based on a minimax entropy theory that the authors studied in modeling t...