000			04842nam a22006375i 4500
001			978-3-540-49430-0
003			DE-He213
005			20240423132437.0
007			cr nn 008mamaa
008			121227s1998 gw | s |||| 0|eng d
020			_a9783540494300 _9978-3-540-49430-0
024	7		_a10.1007/3-540-49430-8 _2doi
050		4	_aQA75.5-76.95
072		7	_aUYA _2bicssc
072		7	_aCOM014000 _2bisacsh
072		7	_aUYA _2thema
082	0	4	_a004.0151 _223
245	1	0	_aNeural Networks: Tricks of the Trade _h[electronic resource] / _cedited by Genevieve B. Orr, Klaus-Robert Müller.
250			_a1st ed. 1998.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c1998.
300			_aVIII, 432 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aLecture Notes in Computer Science, _x1611-3349 ; _v1524
505	0		_aSpeeding Learning -- Efficient BackProp -- Regularization Techniques to Improve Generalization -- Early Stopping - But When? -- A Simple Trick for Estimating the Weight Decay Parameter -- Controlling the hyperparameter search in MacKay’s Bayesian neural network framework -- Adaptive Regularization in Neural Network Modeling -- Large Ensemble Averaging -- Improving Network Models and Algorithmic Tricks -- Square Unit Augmented Radially Extended Multilayer Perceptrons -- A Dozen Tricks with Multitask Learning -- Solving the Ill-Conditioning in Neural Network Learning -- Centering Neural Network Gradient Factors -- Avoiding roundoff error in backpropagating derivatives -- Representing and Incorporating Prior Knowledge in Neural Network Training -- Transformation Invariance in Pattern Recognition — Tangent Distance and Tangent Propagation -- Combining Neural Networks and Context-Driven Search for Online, Printed Handwriting Recognition in the Newton -- Neural Network Classification and Prior Class Probabilities -- Applying Divide and Conquer to Large Scale Pattern Recognition Tasks -- Tricks for Time Series -- Forecasting the Economy with Neural Nets: A Survey of Challenges and Solutions -- How to Train Neural Networks.
520			_aIt is our belief that researchers and practitioners acquire, through experience and word-of-mouth, techniques and heuristics that help them successfully apply neural networks to di cult real world problems. Often these \tricks" are theo- tically well motivated. Sometimes they are the result of trial and error. However, their most common link is that they are usually hidden in people’s heads or in the back pages of space-constrained conference papers. As a result newcomers to the eld waste much time wondering why their networks train so slowly and perform so poorly. This book is an outgrowth of a 1996 NIPS workshop called Tricks of the Trade whose goal was to begin the process of gathering and documenting these tricks. The interest that the workshop generated motivated us to expand our collection and compile it into this book. Although we have no doubt that there are many tricks we have missed, we hope that what we have included will prove to be useful, particularly to those who are relatively new to the eld. Each chapter contains one or more tricks presented by a given author (or authors). We have attempted to group related chapters into sections, though we recognize that the di erent sections are far from disjoint. Some of the chapters (e.g., 1, 13, 17) contain entire systems of tricks that are far more general than the category they have been placed in.
650		0	_aComputer science.
650		0	_aArtificial intelligence.
650		0	_aMicroprocessors.
650		0	_aComputer architecture.
650		0	_aPattern recognition systems.
650		0	_aDynamics.
650		0	_aNonlinear theories.
650	1	4	_aTheory of Computation.
650	2	4	_aArtificial Intelligence.
650	2	4	_aProcessor Architectures.
650	2	4	_aAutomated Pattern Recognition.
650	2	4	_aApplied Dynamical Systems.
700	1		_aOrr, Genevieve B. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aMüller, Klaus-Robert. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
710	2		_aSpringerLink (Online service)
773	0		_tSpringer Nature eBook
776	0	8	_iPrinted edition: _z9783540653110
776	0	8	_iPrinted edition: _z9783662198131
830		0	_aLecture Notes in Computer Science, _x1611-3349 ; _v1524
856	4	0	_uhttps://doi.org/10.1007/3-540-49430-8
912			_aZDB-2-SCS
912			_aZDB-2-SXCS
912			_aZDB-2-LNC
912			_aZDB-2-BAE
942			_cSPRINGER
999			_c187818 _d187818