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IWANN
2001
Springer
14 years 9 days ago
A Penalization Criterion Based on Noise Behaviour for Model Selection
Complexity-penalization strategies are one way to decide on the most appropriate network size in order to address the trade-off between overfitted and underfitted models. In this p...
Joaquín Pizarro Junquera, Pedro Galindo Ria...
ICMLA
2007
13 years 9 months ago
Improving gene expression programming performance by using differential evolution
Gene Expression Programming (GEP) is an evolutionary algorithm that incorporates both the idea of a simple, linear chromosome of fixed length used in Genetic Algorithms (GAs) and...
Qiongyun Zhang, Chi Zhou, Weimin Xiao, Peter C. Ne...
AAAI
2006
13 years 9 months ago
Multi-Conditional Learning: Generative/Discriminative Training for Clustering and Classification
This paper presents multi-conditional learning (MCL), a training criterion based on a product of multiple conditional likelihoods. When combining the traditional conditional proba...
Andrew McCallum, Chris Pal, Gregory Druck, Xuerui ...
PAMI
2006
114views more  PAMI 2006»
13 years 7 months ago
Nonparametric Supervised Learning by Linear Interpolation with Maximum Entropy
Nonparametric neighborhood methods for learning entail estimation of class conditional probabilities based on relative frequencies of samples that are "near-neighbors" of...
Maya R. Gupta, Robert M. Gray, Richard A. Olshen
PAMI
2010
132views more  PAMI 2010»
13 years 6 months ago
Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters
—Adapting the hyperparameters of support vector machines (SVMs) is a challenging model selection problem, especially when flexible kernels are to be adapted and data are scarce....
Tobias Glasmachers, Christian Igel