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JMLR
2012
13 years 9 months ago
Deep Boltzmann Machines as Feed-Forward Hierarchies
The deep Boltzmann machine is a powerful model that extracts the hierarchical structure of observed data. While inference is typically slow due to its undirected nature, we argue ...
Grégoire Montavon, Mikio L. Braun, Klaus-Ro...
ACL
2012
13 years 9 months ago
Head-driven Transition-based Parsing with Top-down Prediction
This paper presents a novel top-down headdriven parsing algorithm for data-driven projective dependency analysis. This algorithm handles global structures, such as clause and coor...
Katsuhiko Hayashi, Taro Watanabe, Masayuki Asahara...
CLUSTER
2007
IEEE
16 years 1 months ago
Sequential and parallel implementation of a constraint-based algorithm for searching protein structures
— Data mining in biological structure libraries can be a powerful tool to better understand biochemical processes. This article introduces the LISA algorithm which enables the re...
Sascha Hunold, Thomas Rauber, Georg Wille
ECCV
1990
Springer
16 years 8 months ago
Finding Geometric and Relational Structures in an Image
Abstract We present a method for extracting geometric and relational structures from raw intensity data. On one hand, low-level image processing extracts isolated features. On the ...
Radu Horaud, Francoise Veillon, Thomas Skordas
ICML
2009
IEEE
16 years 7 months ago
Structure learning of Bayesian networks using constraints
This paper addresses exact learning of Bayesian network structure from data and expert's knowledge based on score functions that are decomposable. First, it describes useful ...
Cassio Polpo de Campos, Zhi Zeng, Qiang Ji