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Learning Theory and Kernel Machines

Overview of attention for book
Cover of 'Learning Theory and Kernel Machines'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Tutorial: Learning Topics in Game-Theoretic Decision Making
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    Chapter 2 A General Class of No-Regret Learning Algorithms and Game-Theoretic Equilibria
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    Chapter 3 Preference Elicitation and Query Learning
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    Chapter 4 Efficient Algorithms for Online Decision Problems
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    Chapter 5 Positive Definite Rational Kernels
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    Chapter 6 Bhattacharyya and Expected Likelihood Kernels
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    Chapter 7 Maximal Margin Classification for Metric Spaces
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    Chapter 8 Maximum Margin Algorithms with Boolean Kernels
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    Chapter 9 Knowledge-Based Nonlinear Kernel Classifiers
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    Chapter 10 Fast Kernels for Inexact String Matching
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    Chapter 11 On Graph Kernels: Hardness Results and Efficient Alternatives
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    Chapter 12 Kernels and Regularization on Graphs
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    Chapter 13 Data-Dependent Bounds for Multi-category Classification Based on Convex Losses
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    Chapter 14 Comparing Clusterings by the Variation of Information
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    Chapter 15 Multiplicative Updates for Large Margin Classifiers
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    Chapter 16 Simplified PAC-Bayesian Margin Bounds
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    Chapter 17 Sparse Kernel Partial Least Squares Regression
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    Chapter 18 Sparse Probability Regression by Label Partitioning
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    Chapter 19 Learning with Rigorous Support Vector Machines
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    Chapter 20 Robust Regression by Boosting the Median
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    Chapter 21 Boosting with Diverse Base Classifiers
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    Chapter 22 Reducing Kernel Matrix Diagonal Dominance Using Semi-definite Programming
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    Chapter 23 Optimal Rates of Aggregation
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    Chapter 24 Distance-Based Classification with Lipschitz Functions
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    Chapter 25 Random Subclass Bounds
  27. Altmetric Badge
    Chapter 26 PAC-MDL Bounds
  28. Altmetric Badge
    Chapter 27 Universal Well-Calibrated Algorithm for On-Line Classification
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    Chapter 28 Learning Probabilistic Linear-Threshold Classifiers via Selective Sampling
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    Chapter 29 Learning Algorithms for Enclosing Points in Bregmanian Spheres
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    Chapter 30 Internal Regret in On-Line Portfolio Selection
  32. Altmetric Badge
    Chapter 31 Lower Bounds on the Sample Complexity of Exploration in the Multi-armed Bandit Problem
  33. Altmetric Badge
    Chapter 32 Smooth ε -Insensitive Regression by Loss Symmetrization
  34. Altmetric Badge
    Chapter 33 On Finding Large Conjunctive Clusters
  35. Altmetric Badge
    Chapter 34 Learning Arithmetic Circuits via Partial Derivatives
  36. Altmetric Badge
    Chapter 35 Using a Linear Fit to Determine Monotonicity Directions
  37. Altmetric Badge
    Chapter 36 Generalization Bounds for Voting Classifiers Based on Sparsity and Clustering
  38. Altmetric Badge
    Chapter 37 Sequence Prediction Based on Monotone Complexity
  39. Altmetric Badge
    Chapter 38 How Many Strings Are Easy to Predict?
  40. Altmetric Badge
    Chapter 39 Polynomial Certificates for Propositional Classes
  41. Altmetric Badge
    Chapter 40 On-Line Learning with Imperfect Monitoring
  42. Altmetric Badge
    Chapter 41 Exploiting Task Relatedness for Multiple Task Learning
  43. Altmetric Badge
    Chapter 42 Approximate Equivalence of Markov Decision Processes
  44. Altmetric Badge
    Chapter 43 An Information Theoretic Tradeoff between Complexity and Accuracy
  45. Altmetric Badge
    Chapter 44 Learning Random Log-Depth Decision Trees under the Uniform Distribution
  46. Altmetric Badge
    Chapter 45 Projective DNF Formulae and Their Revision
  47. Altmetric Badge
    Chapter 46 Learning with Equivalence Constraints and the Relation to Multiclass Learning
  48. Altmetric Badge
    Chapter 47 Tutorial: Machine Learning Methods in Natural Language Processing
  49. Altmetric Badge
    Chapter 48 Learning from Uncertain Data
  50. Altmetric Badge
    Chapter 49 Learning and Parsing Stochastic Unification-Based Grammars
  51. Altmetric Badge
    Chapter 50 Generality’s Price
  52. Altmetric Badge
    Chapter 51 On Learning to Coordinate
  53. Altmetric Badge
    Chapter 52 Learning All Subfunctions of a Function
  54. Altmetric Badge
    Chapter 53 When Is Small Beautiful?
  55. Altmetric Badge
    Chapter 54 Learning a Function of r Relevant Variables
  56. Altmetric Badge
    Chapter 55 Subspace Detection: A Robust Statistics Formulation
  57. Altmetric Badge
    Chapter 56 How Fast Is k -Means?
  58. Altmetric Badge
    Chapter 57 Universal Coding of Zipf Distributions
  59. Altmetric Badge
    Chapter 58 An Open Problem Regarding the Convergence of Universal A Priori Probability
  60. Altmetric Badge
    Chapter 59 Entropy Bounds for Restricted Convex Hulls
  61. Altmetric Badge
    Chapter 60 Compressing to VC Dimension Many Points
Attention for Chapter 14: Comparing Clusterings by the Variation of Information
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About this Attention Score

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

Mentioned by

wikipedia
4 Wikipedia pages

Citations

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23 Dimensions

Readers on

mendeley
257 Mendeley
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3 CiteULike
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Chapter title
Comparing Clusterings by the Variation of Information
Chapter number 14
Book title
Learning Theory and Kernel Machines
Published in
Lecture notes in computer science, February 2016
DOI 10.1007/978-3-540-45167-9_14
Book ISBNs
978-3-54-040720-1, 978-3-54-045167-9
Authors

Marina Meilă

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 257 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 8 3%
Germany 6 2%
France 3 1%
Malaysia 2 <1%
Portugal 2 <1%
Réunion 1 <1%
Ireland 1 <1%
Turkey 1 <1%
Austria 1 <1%
Other 7 3%
Unknown 225 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 87 34%
Student > Master 40 16%
Researcher 39 15%
Student > Bachelor 18 7%
Student > Doctoral Student 14 5%
Other 35 14%
Unknown 24 9%
Readers by discipline Count As %
Computer Science 96 37%
Engineering 33 13%
Agricultural and Biological Sciences 16 6%
Mathematics 12 5%
Physics and Astronomy 9 4%
Other 53 21%
Unknown 38 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 29 June 2018.
All research outputs
#7,452,489
of 22,783,848 outputs
Outputs from Lecture notes in computer science
#2,485
of 8,124 outputs
Outputs of similar age
#127,753
of 400,618 outputs
Outputs of similar age from Lecture notes in computer science
#242
of 531 outputs
Altmetric has tracked 22,783,848 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,124 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 55% 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 400,618 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 55% of its contemporaries.
We're also able to compare this research output to 531 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.