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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
  9. Altmetric Badge
    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
  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
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    Chapter 19 Neural Network Classification and Prior Class Probabilities
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    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
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    Chapter 25 Stochastic Gradient Descent Tricks
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    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
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    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
  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
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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 5: Early Stopping — But When?
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
1 X user
patent
1 patent
wikipedia
10 Wikipedia pages

Citations

dimensions_citation
382 Dimensions

Readers on

mendeley
748 Mendeley
citeulike
3 CiteULike
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Chapter title
Early Stopping — But When?
Chapter number 5
Book title
Neural Networks: Tricks of the Trade
Published in
Lecture notes in computer science, January 2016
DOI 10.1007/978-3-642-35289-8_5
Book ISBNs
978-3-64-235288-1, 978-3-64-235289-8
Authors

Lutz Prechelt, Prechelt, Lutz

Editors

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

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 748 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 <1%
United Kingdom 4 <1%
France 1 <1%
Korea, Republic of 1 <1%
Turkey 1 <1%
Switzerland 1 <1%
Brazil 1 <1%
Japan 1 <1%
Canada 1 <1%
Other 0 0%
Unknown 731 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 169 23%
Student > Ph. D. Student 142 19%
Researcher 83 11%
Student > Bachelor 80 11%
Other 25 3%
Other 62 8%
Unknown 187 25%
Readers by discipline Count As %
Computer Science 243 32%
Engineering 137 18%
Mathematics 19 3%
Physics and Astronomy 16 2%
Earth and Planetary Sciences 14 2%
Other 103 14%
Unknown 216 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 02 December 2023.
All research outputs
#1,775,248
of 25,998,826 outputs
Outputs from Lecture notes in computer science
#280
of 8,225 outputs
Outputs of similar age
#30,590
of 411,504 outputs
Outputs of similar age from Lecture notes in computer science
#63
of 513 outputs
Altmetric has tracked 25,998,826 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,225 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has done particularly well, scoring higher than 96% 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 411,504 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 513 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.