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CPAIOR
2004
Springer
14 years 2 months ago
Scheduling Abstractions for Local Search
ng Abstractions for Local Search Pascal Van Hentenryck1 and Laurent Michel2 1 Brown University, Box 1910, Providence, RI 02912 2 University of Connecticut, Storrs, CT 06269-3155 Ab...
Pascal Van Hentenryck, Laurent Michel
ICDE
2012
IEEE
246views Database» more  ICDE 2012»
11 years 11 months ago
HiCS: High Contrast Subspaces for Density-Based Outlier Ranking
—Outlier mining is a major task in data analysis. Outliers are objects that highly deviate from regular objects in their local neighborhood. Density-based outlier ranking methods...
Fabian Keller, Emmanuel Müller, Klemens B&oum...
UAI
1996
13 years 10 months ago
Learning Equivalence Classes of Bayesian Network Structures
Two Bayesian-network structures are said to be equivalent if the set of distributions that can be represented with one of those structures is identical to the set of distributions...
David Maxwell Chickering
IJAR
2007
130views more  IJAR 2007»
13 years 8 months ago
Bayesian network learning algorithms using structural restrictions
The use of several types of structural restrictions within algorithms for learning Bayesian networks is considered. These restrictions may codify expert knowledge in a given domai...
Luis M. de Campos, Javier Gomez Castellano
SCIA
2009
Springer
140views Image Analysis» more  SCIA 2009»
14 years 3 months ago
Fast Prototype Based Noise Reduction
This paper introduces a novel method for noise reduction in medical images based on concepts of the Non-Local Means algorithm. The main objective has been to develop a method that ...
Kajsa Tibell, Hagen Spies, Magnus Borga