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ECAI
2004
Springer
14 years 2 months ago
Learning Techniques for Automatic Algorithm Portfolio Selection
The purpose of this paper is to show that a well known machine learning technique based on Decision Trees can be effectively used to select the best approach (in terms of efficien...
Alessio Guerri, Michela Milano
GECCO
2008
Springer
118views Optimization» more  GECCO 2008»
13 years 9 months ago
An analysis of multi-sampled issue and no-replacement tournament selection
Standard tournament selection samples individuals with replacement. The sampling-with-replacement strategy has its advantages but also has issues. One of the commonly recognised i...
Huayang Xie, Mengjie Zhang, Peter Andreae, Mark Jo...
FLAIRS
2007
13 years 11 months ago
Learning to Identify Global Bottlenecks in Constraint Satisfaction Search
Using information from failures to guide subsequent search is an important technique for solving combinatorial problems in domains such as boolean satisfiability (SAT) and constr...
Diarmuid Grimes, Richard J. Wallace
CORR
2011
Springer
220views Education» more  CORR 2011»
13 years 3 months ago
On a linear programming approach to the discrete Willmore boundary value problem and generalizations
We consider the problem of finding (possibly non connected) discrete surfaces spanning a finite set of discrete boundary curves in the three-dimensional space and minimizing (glo...
Thomas Schoenemann, Simon Masnou, Daniel Cremers
CVPR
2005
IEEE
14 years 10 months ago
Shape Regularized Active Contour Using Iterative Global Search and Local Optimization
Recently, nonlinear shape models have been shown to improve the robustness and flexibility of segmentation. In this paper, we propose Shape Regularized Active Contour (ShRAC) that...
Tianli Yu, Jiebo Luo, Narendra Ahuja