↓ Skip to main content
What is this page? Embed badge

Oppositional Concepts in Computational Intelligence

Overview of attention for book
Cover of 'Oppositional Concepts in Computational Intelligence'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Introduction
  3. Altmetric Badge
    Chapter 2 Opposition-Based Computing
  4. Altmetric Badge
    Chapter 3 Antithetic and Negatively Associated Random Variables and Function Maximization
  5. Altmetric Badge
    Chapter 4 Opposition and Circularity
  6. Altmetric Badge
    Chapter 5 Collaborative vs. Conflicting Learning, Evolution and Argumentation
  7. Altmetric Badge
    Chapter 6 Proof-Number Search and Its Variants
  8. Altmetric Badge
    Chapter 7 Improving the Exploration Ability of Ant-Based Algorithms
  9. Altmetric Badge
    Chapter 8 Differential Evolution Via Exploiting Opposite Populations
  10. Altmetric Badge
    Chapter 9 Evolving Opposition-Based Pareto Solutions: Multiobjective Optimization Using Competitive Coevolution
  11. Altmetric Badge
    Chapter 10 Bayesian Ying-Yang Harmony Learning for Local Factor Analysis: A Comparative Investigation
  12. Altmetric Badge
    Chapter 11 The Concept of Opposition and Its Use in Q -Learning and Q ( λ ) Techniques
  13. Altmetric Badge
    Chapter 12 Two Frameworks for Improving Gradient-Based Learning Algorithms
  14. Altmetric Badge
    Chapter 13 Opposite Actions in Reinforced Image Segmentation
  15. Altmetric Badge
    Chapter 14 Opposition Mining in Reservoir Management
Attention for Chapter 12: Two Frameworks for Improving Gradient-Based Learning Algorithms
Altmetric Badge

Citations

dimensions_citation
39 Dimensions

Readers on

mendeley
6 Mendeley
Summary Dimensions citations
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
Two Frameworks for Improving Gradient-Based Learning Algorithms
Chapter number 12
Book title
Oppositional Concepts in Computational Intelligence
Published by
Springer, Berlin, Heidelberg, January 2008
DOI 10.1007/978-3-540-70829-2_12
Book ISBNs
978-3-54-070826-1, 978-3-54-070829-2
Authors

Mario Ventresca, H. R. Tizhoosh

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 33%
Professor > Associate Professor 1 17%
Professor 1 17%
Unknown 2 33%
Readers by discipline Count As %
Computer Science 4 67%
Unknown 2 33%

This page is provided by Altmetric.