A cascade model is a rule induction methodology using levelwise expansion of an itemset lattice, where the explanatory power of a rule set and its constituent rules are quantitativ...
Abstract. In this paper, we propose a new approach to learn structured visual compound models from shape-based feature descriptions. We use captioned text in order to drive the pro...
Jan Moringen, Sven Wachsmuth, Sven J. Dickinson, S...
We use a generative history-based model to predict the most likely derivation of a dependency parse. Our probabilistic model is based on Incremental Sigmoid Belief Networks, a rec...
In this paper, we present a systems approach for channel modeling of an Automatic Speech Recognition (ASR) system. This can have implications in improving speech recognition compo...
Qun Feng Tan, Kartik Audhkhasi, Panayiotis G. Geor...
In this paper, we propose a probabilistic model for web image mining, which is based on concept-sensitive salient regions without human intervene. Our goal is to achieve a middle-...