Neural Networks: Tricks of the Trade (Record no. 103844)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 05029nam a22005775i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-642-35289-8 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20140220083331.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 121116s2012 gw | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9783642352898 |
| -- | 978-3-642-35289-8 |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 10.1007/978-3-642-35289-8 |
| Source of number or code | doi |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | QA75.5-76.95 |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UYZG |
| Source | bicssc |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | COM037000 |
| Source | bisacsh |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 004.0151 |
| Edition number | 23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Montavon, Grégoire. |
| Relator term | editor. |
| 245 10 - TITLE STATEMENT | |
| Title | Neural Networks: Tricks of the Trade |
| Medium | [electronic resource] : |
| Remainder of title | Second Edition / |
| Statement of responsibility, etc | edited by Grégoire Montavon, Geneviève B. Orr, Klaus-Robert Müller. |
| 264 #1 - | |
| -- | Berlin, Heidelberg : |
| -- | Springer Berlin Heidelberg : |
| -- | Imprint: Springer, |
| -- | 2012. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | XII, 769 p. 223 illus. |
| Other physical details | online resource. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 490 1# - SERIES STATEMENT | |
| Series statement | Lecture Notes in Computer Science, |
| International Standard Serial Number | 0302-9743 ; |
| Volume number/sequential designation | 7700 |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Introduction -- Preface on Speeding Learning -- 1. Efficient BackProp -- Preface on Regularization Techniques to Improve Generalization -- 2. Early Stopping — But When? -- 3. A Simple Trick for Estimating the Weight Decay Parameter -- 4. Controlling the Hyperparameter Search in MacKay’s Bayesian Neural Network Framework.- 5. Adaptive Regularization in Neural Network Modeling -- 6. Large Ensemble Averaging -- Preface on Improving Network Models and Algorithmic Tricks -- 7. Square Unit Augmented, Radially Extended, Multilayer Perceptrons -- 8. A Dozen Tricks with Multitask Learning -- 9. Solving the Ill-Conditioning in Neural Network Learning -- 10. Centering Neural Network Gradient Factors -- 11. Avoiding Roundoff Error in Backpropagating Derivatives.- 12. Transformation Invariance in Pattern Recognition –Tangent Distance and Tangent Propagation -- 13. Combining Neural Networks and Context-Driven Search for On-line, Printed Handwriting Recognition in the Newtons -- 14. Neural Network Classification and Prior Class Probabilities -- 15. Applying Divide and Conquer to Large Scale Pattern Recognition Tasks -- Preface on Tricks for Time Series -- 16. Forecasting the Economy with Neural Nets: A Survey of Challenges and Solutions -- 17. How to Train Neural Networks -- Preface on Big Learning in Deep Neural Networks -- 18. Stochastic Gradient Descent Tricks.- 19. Practical Recommendations for Gradient-Based Training of Deep Architectures -- 20. Training Deep and Recurrent Networks with Hessian-Free Optimization -- 21. Implementing Neural Networks Efficiently -- Preface on Better Representations: Invariant, Disentangled and Reusable -- 22. Learning Feature Representations with K-Means -- 23. Deep Big Multilayer Perceptrons for Digit Recognition -- 24. A Practical Guide to Training Restricted Boltzmann Machines -- 25. Deep Boltzmann Machines and the Centering Trick -- 26. Deep Learning via Semi-supervised Embedding -- Preface on Identifying Dynamical Systems for Forecasting and Control -- 27. A Practical Guide to Applying Echo State Networks -- 28. Forecasting with Recurrent Neural Networks: 12 Tricks -- 29. Solving Partially Observable Reinforcement Learning Problems with Recurrent Neural Networks -- 30. 10 Steps and Some Tricks to Set up Neural Reinforcement Controllers. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | The twenty last years have been marked by an increase in available data and computing power. In parallel to this trend, the focus of neural network research and the practice of training neural networks has undergone a number of important changes, for example, use of deep learning machines. The second edition of the book augments the first edition with more tricks, which have resulted from 14 years of theory and experimentation by some of the world's most prominent neural network researchers. These tricks can make a substantial difference (in terms of speed, ease of implementation, and accuracy) when it comes to putting algorithms to work on real problems. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer science. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer software. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Artificial intelligence. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Optical pattern recognition. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Physics. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Engineering. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer Science. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computation by Abstract Devices. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Artificial Intelligence (incl. Robotics). |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Algorithm Analysis and Problem Complexity. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Pattern Recognition. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Complexity. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Information Systems Applications (incl. Internet). |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Orr, Geneviève B. |
| Relator term | editor. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Müller, Klaus-Robert. |
| Relator term | editor. |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY | |
| Title | Springer eBooks |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Display text | Printed edition: |
| International Standard Book Number | 9783642352881 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| Uniform title | Lecture Notes in Computer Science, |
| -- | 0302-9743 ; |
| Volume number/sequential designation | 7700 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | http://dx.doi.org/10.1007/978-3-642-35289-8 |
| 912 ## - | |
| -- | ZDB-2-SCS |
| 912 ## - | |
| -- | ZDB-2-LNC |
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