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Recent Advances in Big Data and Deep Learning

Overview of attention for book
Cover of 'Recent Advances in Big Data and Deep Learning'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 On the Trade-Off Between Number of Examples and Precision of Supervision in Regression
  3. Altmetric Badge
    Chapter 2 Distributed SmSVM Ensemble Learning
  4. Altmetric Badge
    Chapter 3 Size/Accuracy Trade-Off in Convolutional Neural Networks: An Evolutionary Approach
  5. Altmetric Badge
    Chapter 4 Fast Transfer Learning for Image Polarity Detection
  6. Altmetric Badge
    Chapter 5 Dropout for Recurrent Neural Networks
  7. Altmetric Badge
    Chapter 6 Psychiatric Disorders Classification with 3D Convolutional Neural Networks
  8. Altmetric Badge
    Chapter 7 Perturbed Proximal Descent to Escape Saddle Points for Non-convex and Non-smooth Objective Functions
  9. Altmetric Badge
    Chapter 8 Deep-Learning Domain Adaptation Techniques for Credit Cards Fraud Detection
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    Chapter 9 Selective Information Extraction Strategies for Cancer Pathology Reports with Convolutional Neural Networks
  11. Altmetric Badge
    Chapter 10 An Information Theoretic Approach to the Autoencoder
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    Chapter 11 Deep Regression Counting: Customized Datasets and Inter-Architecture Transfer Learning
  13. Altmetric Badge
    Chapter 12 Improving Railway Maintenance Actions with Big Data and Distributed Ledger Technologies
  14. Altmetric Badge
    Chapter 13 Presumable Applications of Deep Learning for Cellular Automata Identification
  15. Altmetric Badge
    Chapter 14 Restoration Time Prediction in Large Scale Railway Networks: Big Data and Interpretability
  16. Altmetric Badge
    Chapter 15 Train Overtaking Prediction in Railway Networks: A Big Data Perspective
  17. Altmetric Badge
    Chapter 16 Cavitation Noise Spectra Prediction with Hybrid Models
  18. Altmetric Badge
    Chapter 17 Pseudoinverse Learners: New Trend and Applications to Big Data
  19. Altmetric Badge
    Chapter 18 Innovation Capability of Firms: A Big Data Approach with Patents
  20. Altmetric Badge
    Chapter 19 Predicting Future Market Trends: Which Is the Optimal Window?
  21. Altmetric Badge
    Chapter 20 $$F_{0}$$ F 0 Modeling Using DNN for Arabic Parametric Speech Synthesis
  22. Altmetric Badge
    Chapter 21 Regularizing Neural Networks with Gradient Monitoring
  23. Altmetric Badge
    Chapter 22 Visual Analytics for Supporting Conflict Resolution in Large Railway Networks
  24. Altmetric Badge
    Chapter 23 Modeling Urban Traffic Data Through Graph-Based Neural Networks
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    Chapter 24 Traffic Sign Detection Using R-CNN
  26. Altmetric Badge
    Chapter 25 Deep Tree Transductions - A Short Survey
  27. Altmetric Badge
    Chapter 26 Approximating the Solution of Surface Wave Propagation Using Deep Neural Networks
  28. Altmetric Badge
    Chapter 27 A Semi-supervised Deep Rule-Based Approach for Remote Sensing Scene Classification
  29. Altmetric Badge
    Chapter 28 Comparing the Estimations of Value-at-Risk Using Artificial Network and Other Methods for Business Sectors
  30. Altmetric Badge
    Chapter 29 Using Convolutional Neural Networks to Distinguish Different Sign Language Alphanumerics
  31. Altmetric Badge
    Chapter 30 Mise en abyme with Artificial Intelligence: How to Predict the Accuracy of NN, Applied to Hyper-parameter Tuning
  32. Altmetric Badge
    Chapter 31 Asynchronous Stochastic Variational Inference
  33. Altmetric Badge
    Chapter 32 Probabilistic Bounds for Binary Classification of Large Data Sets
  34. Altmetric Badge
    Chapter 33 Multikernel Activation Functions: Formulation and a Case Study
  35. Altmetric Badge
    Chapter 34 Understanding Ancient Coin Images
  36. Altmetric Badge
    Chapter 35 Effects of Skip-Connection in ResNet and Batch-Normalization on Fisher Information Matrix
  37. Altmetric Badge
    Chapter 36 Skipping Two Layers in ResNet Makes the Generalization Gap Smaller than Skipping One or No Layer
  38. Altmetric Badge
    Chapter 37 A Preference-Learning Framework for Modeling Relational Data
  39. Altmetric Badge
    Chapter 38 Convolutional Neural Networks for Twitter Text Toxicity Analysis
  40. Altmetric Badge
    Chapter 39 Fast Spectral Radius Initialization for Recurrent Neural Networks
Attention for Chapter 30: Mise en abyme with Artificial Intelligence: How to Predict the Accuracy of NN, Applied to Hyper-parameter Tuning
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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 (64th percentile)

Mentioned by

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3 X users

Citations

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4 Dimensions

Readers on

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2 Mendeley
Summary X Dimensions citations
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Chapter title
Mise en abyme with Artificial Intelligence: How to Predict the Accuracy of NN, Applied to Hyper-parameter Tuning
Chapter number 30
Book title
Recent Advances in Big Data and Deep Learning
Published in
arXiv, April 2019
DOI 10.1007/978-3-030-16841-4_30
Book ISBNs
978-3-03-016840-7, 978-3-03-016841-4
Authors

Giorgia Franchini, Mathilde Galinier, Micaela Verucchi, Franchini, Giorgia, Galinier, Mathilde, Verucchi, Micaela

View on publisher site
X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 50%
Researcher 1 50%
Readers by discipline Count As %
Unspecified 1 50%
Linguistics 1 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 July 2019.
All research outputs
#14,445,514
of 23,140,503 outputs
Outputs from arXiv
#287,417
of 952,409 outputs
Outputs of similar age
#194,225
of 350,169 outputs
Outputs of similar age from arXiv
#8,703
of 27,392 outputs
Altmetric has tracked 23,140,503 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 952,409 research outputs from this source. They receive a mean Attention Score of 3.9. This one has gotten more attention than average, scoring higher than 65% 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 350,169 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 27,392 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 64% of its contemporaries.

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