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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
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    Chapter 2 Distributed SmSVM Ensemble Learning
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    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
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    Chapter 7 Perturbed Proximal Descent to Escape Saddle Points for Non-convex and Non-smooth Objective Functions
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    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
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    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
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    Chapter 12 Improving Railway Maintenance Actions with Big Data and Distributed Ledger Technologies
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    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
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    Chapter 15 Train Overtaking Prediction in Railway Networks: A Big Data Perspective
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    Chapter 16 Cavitation Noise Spectra Prediction with Hybrid Models
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    Chapter 17 Pseudoinverse Learners: New Trend and Applications to Big Data
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    Chapter 18 Innovation Capability of Firms: A Big Data Approach with Patents
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    Chapter 19 Predicting Future Market Trends: Which Is the Optimal Window?
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    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
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    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
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    Chapter 28 Comparing the Estimations of Value-at-Risk Using Artificial Network and Other Methods for Business Sectors
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    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 7: Perturbed Proximal Descent to Escape Saddle Points for Non-convex and Non-smooth Objective Functions
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Chapter title
Perturbed Proximal Descent to Escape Saddle Points for Non-convex and Non-smooth Objective Functions
Chapter number 7
Book title
Recent Advances in Big Data and Deep Learning
Published in
arXiv, April 2019
DOI 10.1007/978-3-030-16841-4_7
Book ISBNs
978-3-03-016840-7, 978-3-03-016841-4
Authors

Zhishen Huang, Stephen Becker, Huang, Zhishen, Becker, Stephen

View on publisher site
X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 27%
Student > Doctoral Student 2 18%
Researcher 2 18%
Professor 1 9%
Student > Bachelor 1 9%
Other 1 9%
Unknown 1 9%
Readers by discipline Count As %
Computer Science 4 36%
Mathematics 3 27%
Engineering 2 18%
Linguistics 1 9%
Unknown 1 9%
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 28 January 2019.
All research outputs
#19,495,804
of 23,978,545 outputs
Outputs from arXiv
#588,045
of 1,010,913 outputs
Outputs of similar age
#268,269
of 353,939 outputs
Outputs of similar age from arXiv
#16,056
of 27,729 outputs
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So far Altmetric has tracked 1,010,913 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 25th percentile – i.e., 25% of its peers scored the same or lower than it.
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 353,939 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 27,729 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.

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