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Stochastic Algorithms: Foundations and Applications

Overview of attention for book
Cover of 'Stochastic Algorithms: Foundations and Applications'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Scenario Reduction Techniques in Stochastic Programming
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    Chapter 2 Statistical Learning of Probabilistic BDDs
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    Chapter 3 Learning Volatility of Discrete Time Series Using Prediction with Expert Advice
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    Chapter 4 Prediction of Long-Range Dependent Time Series Data with Performance Guarantee
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    Chapter 5 Bipartite Graph Representation of Multiple Decision Table Classifiers
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    Chapter 6 Bounds for Multistage Stochastic Programs Using Supervised Learning Strategies
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    Chapter 7 On Evolvability: The Swapping Algorithm, Product Distributions, and Covariance
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    Chapter 8 A Generic Algorithm for Approximately Solving Stochastic Graph Optimization Problems
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    Chapter 9 How to Design a Linear Cover Time Random Walk on a Finite Graph
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    Chapter 10 Propagation Connectivity of Random Hypergraphs
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    Chapter 11 Graph Embedding through Random Walk for Shortest Paths Problems
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    Chapter 12 Relational Properties Expressible with One Universal Quantifier Are Testable
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    Chapter 13 Theoretical Analysis of Local Search in Software Testing
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    Chapter 14 Firefly Algorithms for Multimodal Optimization
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    Chapter 15 Economical Caching with Stochastic Prices
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    Chapter 16 Markov Modelling of Mitochondrial BAK Activation Kinetics during Apoptosis
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    Chapter 17 Stochastic Dynamics of Logistic Tumor Growth
Overall attention for this book and its chapters
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

2 tweeters
1 Wikipedia page


14 Dimensions

Readers on

46 Mendeley
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Stochastic Algorithms: Foundations and Applications
Published by
ADS, January 2009
DOI 10.1007/978-3-642-04944-6
978-3-64-204943-9, 978-3-64-204944-6

Osamu Watanabe, Thomas Zeugmann

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 4%
Estonia 1 2%
India 1 2%
Unknown 42 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 22%
Student > Master 10 22%
Student > Bachelor 6 13%
Researcher 4 9%
Student > Postgraduate 4 9%
Other 5 11%
Unknown 7 15%
Readers by discipline Count As %
Computer Science 18 39%
Engineering 9 20%
Business, Management and Accounting 2 4%
Economics, Econometrics and Finance 2 4%
Pharmacology, Toxicology and Pharmaceutical Science 1 2%
Other 4 9%
Unknown 10 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 14 August 2020.
All research outputs
of 16,197,656 outputs
Outputs from ADS
of 30,177 outputs
Outputs of similar age
of 272,537 outputs
Outputs of similar age from ADS
of 255 outputs
Altmetric has tracked 16,197,656 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 30,177 research outputs from this source. They receive a mean Attention Score of 4.4. This one has done well, scoring higher than 76% 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 272,537 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 255 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.