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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...
KDD
2006
ACM
150views Data Mining» more  KDD 2006»
16 years 7 months ago
Maximally informative k-itemsets and their efficient discovery
In this paper we present a new approach to mining binary data. We treat each binary feature (item) as a means of distinguishing two sets of examples. Our interest is in selecting ...
Arno J. Knobbe, Eric K. Y. Ho
HPCA
2008
IEEE
16 years 7 months ago
Roughness of microarchitectural design topologies and its implications for optimization
Recent advances in statistical inference and machine learning close the divide between simulation and classical optimization, thereby enabling more rigorous and robust microarchit...
Benjamin C. Lee, David M. Brooks
ICDAR
2009
IEEE
16 years 1 months ago
Combination of Measurement-Level Classifiers: Output Normalization by Dynamic Time Warping
Classifier combination is a powerful strategy to support useful solutions in difficult classification problems. Notwithstanding, the effectiveness of a multi-classifier system str...
Giuseppe Pirlo, Donato Impedovo, Claudia Adamita T...
AIME
2009
Springer
16 years 1 months ago
Analysing Clinical Guidelines' Contents with Deontic and Rhetorical Structures
The computerisation of clinical guidelines can greatly benefit from the automatic analysis of their content using Natural Language Processing techniques. Because of the central rol...
Gersende Georg, Hugo Hernault, Marc Cavazza, Helmu...