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142
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CEC
2007
IEEE
15 years 5 months ago
Hybrid optimization using DIRECT, GA, and SQP for global exploration
— As there are many good optimization algorithms each with its own characteristics, it is very difficult to choose the best method for optimization problems. Thus, it is importa...
Satoru Hiwa, Tomoyuki Hiroyasu, Mitsunori Miki
CP
2009
Springer
16 years 4 months ago
Filtering Numerical CSPs Using Well-Constrained Subsystems
When interval methods handle systems of equations over the reals, two main types of filtering/contraction algorithms are used to reduce the search space. When the system is well-co...
Ignacio Araya, Gilles Trombettoni, Bertrand Neveu
JMLR
2010
149views more  JMLR 2010»
14 years 10 months ago
Learning Bayesian Network Structure using LP Relaxations
We propose to solve the combinatorial problem of finding the highest scoring Bayesian network structure from data. This structure learning problem can be viewed as an inference pr...
Tommi Jaakkola, David Sontag, Amir Globerson, Mari...
KDD
2006
ACM
213views Data Mining» more  KDD 2006»
16 years 4 months ago
Learning sparse metrics via linear programming
Calculation of object similarity, for example through a distance function, is a common part of data mining and machine learning algorithms. This calculation is crucial for efficie...
Glenn Fung, Rómer Rosales
172
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JEI
2006
162views more  JEI 2006»
15 years 3 months ago
Markovian segmentation and parameter estimation on graphics hardware
In this paper, we show how Markovian strategies used to solve well-known segmentation problems such as motion estimation, motion detection, motion segmentation, stereovision, and c...
Pierre-Marc Jodoin, Max Mignotte