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» Optimizing Sorting with Machine Learning Algorithms
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ICML
2009
IEEE
16 years 2 months ago
Learning structural SVMs with latent variables
We present a large-margin formulation and algorithm for structured output prediction that allows the use of latent variables. Our proposal covers a large range of application prob...
Chun-Nam John Yu, Thorsten Joachims
ALGORITHMICA
2010
95views more  ALGORITHMICA 2010»
15 years 2 months ago
Homogeneous String Segmentation using Trees and Weighted Independent Sets
We divide a string into k segments, each with only one sort of symbols, so as to minimize the total number of exceptions. Motivations come from machine learning and data mining. F...
Peter Damaschke
AIEDAM
1998
87views more  AIEDAM 1998»
15 years 1 months ago
Learning to set up numerical optimizations of engineering designs
Gradient-based numerical optimization of complex engineering designs offers the promise of rapidly producing better designs. However, such methods generally assume that the object...
Mark Schwabacher, Thomas Ellman, Haym Hirsh
ICML
2008
IEEE
16 years 2 months ago
Active kernel learning
Identifying the appropriate kernel function/matrix for a given dataset is essential to all kernel-based learning techniques. A variety of kernel learning algorithms have been prop...
Steven C. H. Hoi, Rong Jin
GECCO
2007
Springer
194views Optimization» more  GECCO 2007»
15 years 8 months ago
Hybrid coevolutionary algorithms vs. SVM algorithms
As a learning method support vector machine is regarded as one of the best classifiers with a strong mathematical foundation. On the other hand, evolutionary computational techniq...
Rui Li, Bir Bhanu, Krzysztof Krawiec