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» Anytime Algorithm for Feature Selection
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107
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SYNASC
2005
IEEE
77views Algorithms» more  SYNASC 2005»
15 years 8 months ago
On P Systems with Bounded Parallelism
— A framework that describes the evolution of P systems with bounded parallelism is defined by introducing basic formal features that can be then integrated into a structural op...
Francesco Bernardini, Francisco José Romero...
120
Voted
PKDD
2000
Springer
134views Data Mining» more  PKDD 2000»
15 years 6 months ago
Induction of Multivariate Decision Trees by Using Dipolar Criteria
A new approach to the induction of multivariate decision trees is proposed. A linear decision function (hyper-plane) is used at each non-terminal node of a binary tree for splittin...
Leon Bobrowski, Marek Kretowski
127
Voted
NIPS
2003
15 years 4 months ago
1-norm Support Vector Machines
The standard 2-norm SVM is known for its good performance in twoclass classi£cation. In this paper, we consider the 1-norm SVM. We argue that the 1-norm SVM may have some advanta...
Ji Zhu, Saharon Rosset, Trevor Hastie, Robert Tibs...
166
Voted
EUSFLAT
2009
679views Fuzzy Logic» more  EUSFLAT 2009»
15 years 11 days ago
Combining Wavelets and Computational Intelligence Methods with Applications on Multi-class Classification Datasets
In this paper, we propose a novel algorithm for wavelet feature extraction as input to a supervised Multi-Class Classifier to improve classification performance. In particular, to ...
Carlos Campos Bracho
GECCO
2009
Springer
124views Optimization» more  GECCO 2009»
15 years 7 months ago
Reinforcement learning for games: failures and successes
We apply CMA-ES, an evolution strategy with covariance matrix adaptation, and TDL (Temporal Difference Learning) to reinforcement learning tasks. In both cases these algorithms se...
Wolfgang Konen, Thomas Bartz-Beielstein