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Neural Networks: Tricks of the Trade

Overview of attention for book
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
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    Chapter 7 Controlling the Hyperparameter Search in MacKay’s Bayesian Neural Network Framework
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    Chapter 8 Adaptive Regularization in Neural Network Modeling
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    Chapter 9 Large Ensemble Averaging
  11. Altmetric Badge
    Chapter 10 Improving Network Models and Algorithmic Tricks
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    Chapter 11 Square Unit Augmented, Radially Extended, Multilayer Perceptrons
  13. Altmetric Badge
    Chapter 12 A Dozen Tricks with Multitask Learning
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    Chapter 13 Solving the Ill-Conditioning in Neural Network Learning
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    Chapter 14 Centering Neural Network Gradient Factors
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    Chapter 15 Avoiding Roundoff Error in Backpropagating Derivatives
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    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
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    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
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    Chapter 29 Better Representations: Invariant, Disentangled and Reusable
  31. Altmetric Badge
    Chapter 30 Learning Feature Representations with K-Means
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    Chapter 31 Deep Big Multilayer Perceptrons for Digit Recognition
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    Chapter 32 A Practical Guide to Training Restricted Boltzmann Machines
  34. Altmetric Badge
    Chapter 33 Learning Feature Hierarchies with Centered Deep Boltzmann Machines
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    Chapter 34 Deep Learning via Semi-supervised Embedding
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    Chapter 35 Identifying Dynamical Systems for Forecasting and Control
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    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 38: Solving Partially Observable Reinforcement Learning Problems with Recurrent Neural Networks
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

Mentioned by

patent
2 patents

Citations

dimensions_citation
343 Dimensions

Readers on

mendeley
74 Mendeley
citeulike
1 CiteULike
Summary Patents Dimensions citations
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Chapter title
Solving Partially Observable Reinforcement Learning Problems with Recurrent Neural Networks
Chapter number 38
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_38
Book ISBNs
978-3-64-235288-1, 978-3-64-235289-8
Authors

Siegmund Duell, Steffen Udluft, Volkmar Sterzing, Duell, Siegmund, Udluft, Steffen, Sterzing, Volkmar

Editors

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

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 3%
United Kingdom 1 1%
France 1 1%
Unknown 70 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 27%
Student > Master 17 23%
Researcher 10 14%
Student > Doctoral Student 5 7%
Other 5 7%
Other 7 9%
Unknown 10 14%
Readers by discipline Count As %
Computer Science 33 45%
Engineering 18 24%
Mathematics 3 4%
Agricultural and Biological Sciences 2 3%
Economics, Econometrics and Finance 2 3%
Other 3 4%
Unknown 13 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 04 April 2023.
All research outputs
#7,730,464
of 23,510,717 outputs
Outputs from Lecture notes in computer science
#2,492
of 8,137 outputs
Outputs of similar age
#72,056
of 247,506 outputs
Outputs of similar age from Lecture notes in computer science
#147
of 489 outputs
Altmetric has tracked 23,510,717 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,137 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has gotten more attention than average, scoring higher than 54% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 247,506 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 489 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.

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