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» Neural methods for non-standard data
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ICML
2005
IEEE
16 years 4 months ago
Learning to rank using gradient descent
We investigate using gradient descent methods for learning ranking functions; we propose a simple probabilistic cost function, and we introduce RankNet, an implementation of these...
Christopher J. C. Burges, Tal Shaked, Erin Renshaw...
IJCNN
2006
IEEE
15 years 10 months ago
Tentacled Self-Organizing Map for Effective Data Extraction
— Since we can accumulate a huge amount of data including useless information in these years, it is important to investigate various extraction method of clusters from data inclu...
Haruna Matsushita, Yoshifumi Nishio
ICANN
2001
Springer
15 years 8 months ago
Independent Variable Group Analysis
Humans tend to group together related properties in order to understand complex phenomena. When modeling large problems with limited representational resources, it is important to...
Krista Lagus, Esa Alhoniemi, Harri Valpola
IJCNN
2007
IEEE
15 years 10 months ago
Parallel Learning of Large Fuzzy Cognitive Maps
— Fuzzy Cognitive Maps (FCMs) are a class of discrete-time Artificial Neural Networks that are used to model dynamic systems. A recently introduced supervised learning method, wh...
Wojciech Stach, Lukasz A. Kurgan, Witold Pedrycz
ASIAMS
2008
IEEE
15 years 6 months ago
A Blended Text Mining Method for Authorship Authentication Analysis
The paper elaborates upon the interim results achieved in resolving a few newly discovered 16th century letters now alleged to be written by Queen Mary of Scots (QMS). Despite the...
Philip Sallis, Subana Shanmuganathan