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EUROGP
2007
Springer
126views Optimization» more  EUROGP 2007»
13 years 9 months ago
Training Binary GP Classifiers Efficiently: A Pareto-coevolutionary Approach
The conversion and extension of the Incremental Pareto-Coevolution Archive algorithm (IPCA) into the domain of Genetic Programming classification is presented. In particular, the ...
Michal Lemczyk, Malcolm I. Heywood
CEC
2008
IEEE
13 years 11 months ago
Increasing rule extraction accuracy by post-processing GP trees
—Genetic programming (GP), is a very general and efficient technique, often capable of outperforming more specialized techniques on a variety of tasks. In this paper, we suggest ...
Ulf Johansson, Rikard König, Tuve Löfstr...
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
14 years 5 months ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
CORR
2008
Springer
142views Education» more  CORR 2008»
13 years 5 months ago
A Gaussian Belief Propagation Solver for Large Scale Support Vector Machines
Support vector machines (SVMs) are an extremely successful type of classification and regression algorithms. Building an SVM entails solving a constrained convex quadratic program...
Danny Bickson, Elad Yom-Tov, Danny Dolev
KDD
2006
ACM
201views Data Mining» more  KDD 2006»
14 years 5 months ago
Clustering based large margin classification: a scalable approach using SOCP formulation
This paper presents a novel Second Order Cone Programming (SOCP) formulation for large scale binary classification tasks. Assuming that the class conditional densities are mixture...
J. Saketha Nath, Chiranjib Bhattacharyya, M. Naras...