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High Dimensional Probability VII

Overview of attention for book
Cover of 'High Dimensional Probability VII'

Table of Contents

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    Book Overview
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    Chapter 1 Stability of Cramer’s Characterization of Normal Laws in Information Distances
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    Chapter 2 V.N. Sudakov’s Work on Expected Suprema of Gaussian Processes
  4. Altmetric Badge
    Chapter 3 Optimal Concentration of Information Content for Log-Concave Densities
  5. Altmetric Badge
    Chapter 4 Maximal Inequalities for Dependent Random Variables
  6. Altmetric Badge
    Chapter 5 On the Order of the Central Moments of the Length of the Longest Common Subsequences in Random Words
  7. Altmetric Badge
    Chapter 6 A Weighted Approximation Approach to the Study of the Empirical Wasserstein Distance
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    Chapter 7 On the Product of Random Variables and Moments of Sums Under Dependence
  9. Altmetric Badge
    Chapter 8 The Expected Norm of a Sum of Independent Random Matrices: An Elementary Approach
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    Chapter 9 Fechner’s Distribution and Connections to Skew Brownian Motion
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    Chapter 10 Erdős-Rényi-Type Functional Limit Laws for Renewal Processes
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    Chapter 11 Limit Theorems for Quantile and Depth Regions for Stochastic Processes
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    Chapter 12 In Memory of Wenbo V. Li’s Contributions
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    Chapter 13 Orlicz Integrability of Additive Functionals of Harris Ergodic Markov Chains
  15. Altmetric Badge
    Chapter 14 Bounds for Stochastic Processes on Product Index Spaces
  16. Altmetric Badge
    Chapter 15 Permanental Vectors and Selfdecomposability
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    Chapter 16 Permanental Random Variables, M -Matrices and α -Permanents
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    Chapter 17 Convergence in Law Implies Convergence in Total Variation for Polynomials in Independent Gaussian, Gamma or Beta Random Variables
  19. Altmetric Badge
    Chapter 18 Perturbation of Linear Forms of Singular Vectors Under Gaussian Noise
  20. Altmetric Badge
    Chapter 19 Optimal Kernel Selection for Density Estimation
Attention for Chapter 3: Optimal Concentration of Information Content for Log-Concave Densities
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

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3 X users

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Chapter title
Optimal Concentration of Information Content for Log-Concave Densities
Chapter number 3
Book title
High Dimensional Probability VII
Published in
arXiv, January 2016
DOI 10.1007/978-3-319-40519-3_3
Book ISBNs
978-3-31-940517-9, 978-3-31-940519-3
Authors

Matthieu Fradelizi, Mokshay Madiman, Liyao Wang, Fradelizi, Matthieu, Madiman, Mokshay, Wang, Liyao

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 %
Other 1 50%
Student > Master 1 50%
Readers by discipline Count As %
Physics and Astronomy 1 50%
Engineering 1 50%
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 18 August 2015.
All research outputs
#18,575,287
of 23,852,579 outputs
Outputs from arXiv
#459,025
of 990,619 outputs
Outputs of similar age
#273,374
of 398,538 outputs
Outputs of similar age from arXiv
#4,582
of 13,758 outputs
Altmetric has tracked 23,852,579 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 990,619 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 43rd percentile – i.e., 43% 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 398,538 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 13,758 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 55% of its contemporaries.