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ORCIDNeural Networks: Tricks of the Trade@NIPS 1996
- Genevieve B. Orr, Klaus-Robert Müller
:
Neural Networks: Tricks of the Trade. Lecture Notes in Computer Science 1524, Springer 1998, ISBN 3-540-65311-2
Introduction
- Genevieve B. Orr, Klaus-Robert Müller:
Introduction. 1-5
Speeding Learning
- Genevieve B. Orr, Klaus-Robert Müller:
Speeding Learning: Preface. 7-8 - Yann LeCun, Léon Bottou, Genevieve B. Orr, Klaus-Robert Müller:
Effiicient BackProp. 9-50
Regularization Techniques to Improve Generalization
- Genevieve B. Orr, Klaus-Robert Müller:
Regularization Techniques to Improve Generalization: Preface. 51-54 - Lutz Prechelt:
Early Stopping-But When? 55-69 - Thorsteinn S. Rögnvaldsson:
A Simple Trick for Estimating the Weight Decay Parameter. 71-92 - Tony Plate:
Controling the Hyperparameter Search in MacKay's Bayesian Neural Network Framework. 93-112 - Jan Larsen, Claus Svarer, Lars Nonboe Andersen, Lars Kai Hansen:
Adaptive Regularization in Neural Network Modeling. 113-132 - David Horn, Ury Naftaly, Nathan Intrator:
Large Ensemble Averaging. 133-139
Improving Network Models and Algorithmic Tricks
- Genevieve B. Orr, Klaus-Robert Müller:
Improving Network Models and Algorithmic Tricks: Preface. 141-144 - Gary William Flake:
Square Unit Augmented, Radially Extended, Multilayer Perceptrons. 145-163 - Rich Caruana:
A Dozen Tricks with Multitask Learning. 165-191 - Patrick van der Smagt, Gerd Hirzinger:
Solving the Ill-Conditioning in Neural Network Learning. 193-206 - Nicol N. Schraudolph:
Centering Neural Network Gradient Factors. 207-226 - Tony Plate:
Avoiding Roundoff Error in Backpropagating Derivatives. 227-233
Representing and Incorporating Prior Knowledge in Neural Network Training
- Genevieve B. Orr, Klaus-Robert Müller:
Representing and Incorporating Prior Knowledge in Neural Network Training: Preface. 235-238 - Patrice Y. Simard, Yann LeCun, John S. Denker, Bernard Victorri:
Transformation Invariance in Pattern Recognition-Tangent Distance and Tangent Propagation. 239-27 - Larry S. Yaeger, Brandyn J. Webb, Richard F. Lyon:
Combining Neural Networks and Context-Driven Search for On-Line, Printed Handwriting Recognition in the Newton. 275-298 - Steve Lawrence, Ian Burns, Andrew D. Back, Ah Chung Tsoi, C. Lee Giles:
Neural Network Classification and Prior Class Probabilities. 299-313 - Jürgen Fritsch, Michael Finke:
applying Divide and Conquer to Large Scale Pattern Recognition Tasks. 315-342
Tricks for Time Series
- Genevieve B. Orr, Klaus-Robert Müller:
Tricks for Time Series: Preface. 343-346 - John E. Moody:
Forecasting the Economy with Neural Nets: A Survey of Challenges and Solutions. 347-371 - Ralph Neuneier, Hans-Georg Zimmermann:
How to Train Neural Networks. 373-423
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