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CORR
2010
Springer
150views Education» more  CORR 2010»
13 years 7 months ago
Extraction of Symbolic Rules from Artificial Neural Networks
Although backpropagation ANNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions c...
S. M. Kamruzzaman, Md. Monirul Islam
GECCO
2005
Springer
156views Optimization» more  GECCO 2005»
14 years 1 months ago
Extraction of informative genes from microarray data
Identification of those genes that might anticipate the clinical behavior of different types of cancers is challenging due to availability of a smaller number of patient samples...
Topon Kumar Paul, Hitoshi Iba
AI
2008
Springer
14 years 2 months ago
Verbs Speak Loud: Verb Categories in Learning Polarity and Strength of Opinions
In this work we show that verbs reliably represent texts when machine learning algorithms are used to learn opinions. We identify semantic verb categories that capture essential pr...
Marina Sokolova, Guy Lapalme
ICPR
2008
IEEE
14 years 2 months ago
Object-of-interest extraction by integrating stochastic inference with learnt active shape sketch
This article presents a novel integrated approach to object of interest extraction, including learning to define target pattern and extracting by combining detection and segmenta...
Hongwei Li, Liang Lin, Tianfu Wu, Xiaobai Liu, Lan...
ICANN
2007
Springer
14 years 1 months ago
Generalized Softmax Networks for Non-linear Component Extraction
Abstract. We develop a probabilistic interpretation of non-linear component extraction in neural networks that activate their hidden units according to a softmaxlike mechanism. On ...
Jörg Lücke, Maneesh Sahani