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KDD
2007
ACM
276views Data Mining» more  KDD 2007»
14 years 8 months ago
Nonlinear adaptive distance metric learning for clustering
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu
AIPS
2008
13 years 10 months ago
Using Constraint Networks on Timelines to Model and Solve Planning and Scheduling Problems
In the last decades, there has been an increasing interest in the connection between planning and constraint programming. Several approaches were used, leading to different forms ...
Cédric Pralet, Gérard Verfaillie
CC
1994
Springer
107views System Software» more  CC 1994»
13 years 11 months ago
Solving Demand Versions of Interprocedural Analysis Problems
This paper concerns the solution of demand versions of interprocedural analysis problems. In a demand version of a program-analysis problem, some piece of summary information (e.g...
Thomas W. Reps
ANOR
2011
96views more  ANOR 2011»
13 years 2 months ago
Global propagation of side constraints for solving over-constrained problems
This article deals with the resolution of over-constrained problems using constraint programming, which often imposes to add to the constraint network new side constraints. These ...
Thierry Petit, Emmanuel Poder
STACS
2005
Springer
14 years 1 months ago
Solving Medium-Density Subset Sum Problems in Expected Polynomial Time
The subset sum problem (SSP) (given n numbers and a target bound B, find a subset of the numbers summing to B), is one of the classical NP-hard problems. The hardness of SSP vari...
Abraham Flaxman, Bartosz Przydatek