Connection Science

[Amanda Sharkey]

Announcing:

Connection Science Special Issue.  1997, 9,1.

Combining Artificial Neural Nets: Modular Approaches.

Special Issue Editor: Amanda Sharkey

Editorial Board for Special Issue
Leo Breiman, University of Berkeley, USA.
Nathan Intrator, Tel-Aviv University, Israel.
Robert Jacobs, University of Rochester, USA.
Michael Jordan, MIT, USA.
Paul Munro, University of Pittsburgh, USA.
Michael Perrone, IBM, USA.
David Wolpert, IBM, USA.

Contents: 

Amanda J.C. Sharkey. Modularity, Combining and Artificial Neural Nets, 3-10

Stephen P. Luttrell. Self-organization of Multiple Winner-take-all Neural 
Networks. 11-30

Cesare Furlanello, Diego Giuliani, Edmondo Trentin and Stefano Merler. Speaker
Normalization and Model Selection of Combined Neural Networks. 31-50.

Thierry Catfolis and Kurt Meert. Hybridization and Specialization of Real-time
Recurrent Learning-based Neural Networks.  51-70.

Lucila Ohno-Machado and Mark A. Musen. Modular Neural Networs for Medical
Prognosis: Quantifying the Benefits of Combining Neural Networks for Survival
Prediction. 71-86.

Guszti Bartfai and Roger White. Adaptive Resonance Theory-based Modular
Networks for Incremental Learning of Hierarchical Clusterings 87-112.

Research Notes:
Alex Aussem and Fionn Murtagh. Combining Neural Network Forecasts on Wavelet
transformed Time Series. 113-122.

Colin McCormack. Adaptation of Learning Rule Parameters Using a Meta Neural
Network. 123-136.

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See also Connection Science, 8, 3/4 Combining Artificial Neural Nets: Ensemble
Approaches.

Amanda J.C. Sharkey. On Combining Artificial Neural Nets. 299-314.

Sherif Hashem. Effects of Collinearity on Combining Neural Networks. 315-336.

David W. Opitz & Jude W. Shavlik. Actively Searching for an Effective
Neural Network Ensemble. 337-354.

Yuval Raviv & Nathan Intrator. Bootstrapping with Noise: An Effective
Regularization Technique. 355-372.

Bruce E. Rosen.  Ensemble Learning Using Decorrelated Neural Networks. 373-384.

Kagan Tumer & Joydeep Ghosh.  Error Correlation and Error Reduction in
Ensemble Classifiers. 385-404.

Bambang Parmanto, Paul W. Munro & Howard R. Doyle.  Reducing Variance of
Committee Prediction with Resampling Techniques. 405-426.

Peter A. Zhilkin & Ray L. Somorjai.  Application of Several methods of
Classification Fusion to Magnetic Resonance Spectra. 427-442.