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Neural Networks: Tricks of the Trade

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Cover of 'Neural Networks: Tricks of the Trade'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Introduction
  3. Altmetric Badge
    Chapter 2 Speeding Learning
  4. Altmetric Badge
    Chapter 3 Efficient BackProp
  5. Altmetric Badge
    Chapter 4 Regularization Techniques to Improve Generalization
  6. Altmetric Badge
    Chapter 5 Early Stopping — But When?
  7. Altmetric Badge
    Chapter 6 A Simple Trick for Estimating the Weight Decay Parameter
  8. Altmetric Badge
    Chapter 7 Controlling the Hyperparameter Search in MacKay’s Bayesian Neural Network Framework
  9. Altmetric Badge
    Chapter 8 Adaptive Regularization in Neural Network Modeling
  10. Altmetric Badge
    Chapter 9 Large Ensemble Averaging
  11. Altmetric Badge
    Chapter 10 Improving Network Models and Algorithmic Tricks
  12. Altmetric Badge
    Chapter 11 Square Unit Augmented, Radially Extended, Multilayer Perceptrons
  13. Altmetric Badge
    Chapter 12 A Dozen Tricks with Multitask Learning
  14. Altmetric Badge
    Chapter 13 Solving the Ill-Conditioning in Neural Network Learning
  15. Altmetric Badge
    Chapter 14 Centering Neural Network Gradient Factors
  16. Altmetric Badge
    Chapter 15 Avoiding Roundoff Error in Backpropagating Derivatives
  17. Altmetric Badge
    Chapter 16 Representing and Incorporating Prior Knowledge in Neural Network Training
  18. Altmetric Badge
    Chapter 17 Transformation Invariance in Pattern Recognition – Tangent Distance and Tangent Propagation
  19. Altmetric Badge
    Chapter 18 Combining Neural Networks and Context-Driven Search for On-line, Printed Handwriting Recognition in the Newton
  20. Altmetric Badge
    Chapter 19 Neural Network Classification and Prior Class Probabilities
  21. Altmetric Badge
    Chapter 20 Applying Divide and Conquer to Large Scale Pattern Recognition Tasks
  22. Altmetric Badge
    Chapter 21 Tricks for Time Series
  23. Altmetric Badge
    Chapter 22 Forecasting the Economy with Neural Nets: A Survey of Challenges and Solutions
  24. Altmetric Badge
    Chapter 23 How to Train Neural Networks
  25. Altmetric Badge
    Chapter 24 Big Learning and Deep Neural Networks
  26. Altmetric Badge
    Chapter 25 Stochastic Gradient Descent Tricks
  27. Altmetric Badge
    Chapter 26 Practical Recommendations for Gradient-Based Training of Deep Architectures
  28. Altmetric Badge
    Chapter 27 Training Deep and Recurrent Networks with Hessian-Free Optimization
  29. Altmetric Badge
    Chapter 28 Implementing Neural Networks Efficiently
  30. Altmetric Badge
    Chapter 29 Better Representations: Invariant, Disentangled and Reusable
  31. Altmetric Badge
    Chapter 30 Learning Feature Representations with K-Means
  32. Altmetric Badge
    Chapter 31 Deep Big Multilayer Perceptrons for Digit Recognition
  33. Altmetric Badge
    Chapter 32 A Practical Guide to Training Restricted Boltzmann Machines
  34. Altmetric Badge
    Chapter 33 Learning Feature Hierarchies with Centered Deep Boltzmann Machines
  35. Altmetric Badge
    Chapter 34 Deep Learning via Semi-supervised Embedding
  36. Altmetric Badge
    Chapter 35 Identifying Dynamical Systems for Forecasting and Control
  37. Altmetric Badge
    Chapter 36 A Practical Guide to Applying Echo State Networks
  38. Altmetric Badge
    Chapter 37 Forecasting with Recurrent Neural Networks: 12 Tricks
  39. Altmetric Badge
    Chapter 38 Solving Partially Observable Reinforcement Learning Problems with Recurrent Neural Networks
  40. Altmetric Badge
    Chapter 39 10 Steps and Some Tricks to Set up Neural Reinforcement Controllers
Attention for Chapter 33: Learning Feature Hierarchies with Centered Deep Boltzmann Machines
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Chapter title
Learning Feature Hierarchies with Centered Deep Boltzmann Machines
Chapter number 33
Book title
Neural Networks: Tricks of the Trade
Published in
Lecture notes in computer science, January 2012
DOI 10.1007/978-3-642-35289-8_33
Book ISBNs
978-3-64-235288-1, 978-3-64-235289-8
Authors

Grégoire Montavon, Klaus-Robert Müller, Montavon, Grégoire, Müller, Klaus-Robert

Editors

Grégoire Montavon, Geneviève B. Orr, Klaus-Robert Müller

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 154 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 3%
Canada 2 1%
France 1 <1%
Malaysia 1 <1%
Indonesia 1 <1%
United Kingdom 1 <1%
Unknown 144 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 37 24%
Student > Master 30 19%
Researcher 26 17%
Student > Bachelor 15 10%
Other 8 5%
Other 26 17%
Unknown 12 8%
Readers by discipline Count As %
Computer Science 78 51%
Engineering 27 18%
Mathematics 9 6%
Agricultural and Biological Sciences 4 3%
Physics and Astronomy 4 3%
Other 15 10%
Unknown 17 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 November 2012.
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#17,463,699
of 25,617,409 outputs
Outputs from Lecture notes in computer science
#4,762
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Outputs of similar age
#173,565
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Outputs of similar age from Lecture notes in computer science
#269
of 485 outputs
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