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GECCO
2008
Springer
118views Optimization» more  GECCO 2008»
13 years 9 months ago
Unsupervised learning of echo state networks: balancing the double pole
A possible alternative to fine topology tuning for Neural Network (NN) optimization is to use Echo State Networks (ESNs), recurrent NNs built upon a large reservoir of sparsely r...
Fei Jiang, Hugues Berry, Marc Schoenauer
AAAI
2004
13 years 10 months ago
Distributed Representation of Syntactic Structure by Tensor Product Representation and Non-Linear Compression
Representing lexicons and sentences with the subsymbolic approach (using techniques such as Self Organizing Map (SOM) or Artificial Neural Network (ANN)) is a relatively new but i...
Heidi H. T. Yeung, Peter W. M. Tsang
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
14 years 9 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
IJON
2002
185views more  IJON 2002»
13 years 8 months ago
An image retrieval system by impression words and specific object names - IRIS
Image content analysis has become an important issue in multimedia processing. Region-based image retrieval systems attempt to reduce the gap between high-level semantics and low-l...
Kazuhiro Kuroda, Masafumi Hagiwara
IJCNN
2007
IEEE
14 years 3 months ago
TRUST-TECH Based Neural Network Training
— Efficient Training in a neural network plays a vital role in deciding the network architecture and the accuracy of these classifiers. Most popular local training algorithms t...
Hsiao-Dong Chiang, Chandan K. Reddy