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» On the Use of Evidence in Neural Networks
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ICANN
2007
Springer
15 years 8 months ago
Selection of Basis Functions Guided by the L2 Soft Margin
Support Vector Machines (SVMs) for classification tasks produce sparse models by maximizing the margin. Two limitations of this technique are considered in this work: firstly, th...
Ignacio Barrio, Enrique Romero, Lluís Belan...
103
Voted
IJCNN
2006
IEEE
15 years 7 months ago
Learning to Segment Any Random Vector
— We propose a method that takes observations of a random vector as input, and learns to segment each observation into two disjoint parts. We show how to use the internal coheren...
Aapo Hyvärinen, Jukka Perkiö
BMCBI
2010
103views more  BMCBI 2010»
15 years 1 months ago
Prediction of GTP interacting residues, dipeptides and tripeptides in a protein from its evolutionary information
Background: Guanosine triphosphate (GTP)-binding proteins play an important role in regulation of G-protein. Thus prediction of GTP interacting residues in a protein is one of the...
Jagat S. Chauhan, Nitish K. Mishra, Gajendra P. S....
103
Voted
JIPS
2006
72views more  JIPS 2006»
15 years 1 months ago
A Feature Selection Technique based on Distributional Differences
: This paper presents a feature selection technique based on distributional differences for efficient machine learning. Initial training data consists of data including many featur...
Sung-Dong Kim
105
Voted
ICIP
1997
IEEE
16 years 3 months ago
Surrounding Region Dependence Method for Detection of Clustered Microcalcifications on Mammograms
Clustered microcalcifications on X-ray mammograms are an important feature in the detection of breast cancer. For the detection of the clustered microcalcifications on digitized m...
Jong-Kook Kim, Hyun Wook Park