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JMLR
2010
149views more  JMLR 2010»
12 years 11 months ago
Fast Committee-Based Structure Learning
Current methods for causal structure learning tend to be computationally intensive or intractable for large datasets. Some recent approaches have speeded up the process by first m...
Ernest Mwebaze, John A. Quinn
KDD
2010
ACM
274views Data Mining» more  KDD 2010»
13 years 8 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
KDD
1998
ACM
147views Data Mining» more  KDD 1998»
13 years 9 months ago
ADtrees for Fast Counting and for Fast Learning of Association Rules
Abstract: The problem of discovering association rules in large databases has received considerable research attention. Much research has examined the exhaustive discovery of all a...
Brigham S. Anderson, Andrew W. Moore
ESANN
2006
13 years 6 months ago
An algorithm for fast and reliable ESOM learning
The training of Emergent Self-organizing Maps (ESOM ) with large datasets can be a computationally demanding task. Batch learning may be used to speed up training. It is demonstrat...
Mario Nöcker, Fabian Mörchen, Alfred Ult...
IJCV
2010
186views more  IJCV 2010»
13 years 3 months ago
An Approach to the Parameterization of Structure for Fast Categorization
A decomposition is described, which parameterizes the geometry and appearance of contours and regions of gray-scale images with the goal of fast categorization. To express the con...
Christoph Rasche