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Machine learning and knowledge discovery in databases : European conference, ECML PKDD 2008, Antwerp, Belgium, September 15-19, 2008 : proceedings

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Cover of 'Machine learning and knowledge discovery in databases : European conference, ECML PKDD 2008, Antwerp, Belgium, September 15-19, 2008 : proceedings'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Exceptional Model Mining
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    Chapter 2 A Joint Topic and Perspective Model for Ideological Discourse
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    Chapter 3 Effective Pruning Techniques for Mining Quasi-Cliques
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    Chapter 4 Efficient Pairwise Multilabel Classification for Large-Scale Problems in the Legal Domain
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    Chapter 5 Fitted Natural Actor-Critic: A New Algorithm for Continuous State-Action MDPs
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    Chapter 6 A New Natural Policy Gradient by Stationary Distribution Metric
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    Chapter 7 Towards Machine Learning of Grammars and Compilers of Programming Languages
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    Chapter 8 Improving Classification with Pairwise Constraints: A Margin-Based Approach
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    Chapter 9 Metric Learning: A Support Vector Approach
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    Chapter 10 Support Vector Machines, Data Reduction, and Approximate Kernel Matrices
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    Chapter 11 Mixed Bregman Clustering with Approximation Guarantees
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    Chapter 12 Hierarchical, Parameter-Free Community Discovery
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    Chapter 13 A Genetic Algorithm for Text Classification Rule Induction
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    Chapter 14 Nonstationary Gaussian Process Regression Using Point Estimates of Local Smoothness
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    Chapter 15 Kernel-Based Inductive Transfer
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    Chapter 16 State-Dependent Exploration for Policy Gradient Methods
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    Chapter 17 Client-Friendly Classification over Random Hyperplane Hashes
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    Chapter 18 Large-Scale Clustering through Functional Embedding
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    Chapter 19 Clustering Distributed Sensor Data Streams
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    Chapter 20 A Novel Scalable and Data Efficient Feature Subset Selection Algorithm
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    Chapter 21 Robust Feature Selection Using Ensemble Feature Selection Techniques
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    Chapter 22 Effective Visualization of Information Diffusion Process over Complex Networks
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    Chapter 23 Actively Transfer Domain Knowledge
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    Chapter 24 A Unified View of Matrix Factorization Models
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    Chapter 25 Parallel Spectral Clustering
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    Chapter 26 Classification of Multi-labeled Data: A Generative Approach
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    Chapter 27 Pool-Based Agnostic Experiment Design in Linear Regression
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    Chapter 28 Distribution-Free Learning of Bayesian Network Structure
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    Chapter 29 Assessing Nonlinear Granger Causality from Multivariate Time Series
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    Chapter 30 Clustering Via Local Regression
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    Chapter 31 Decomposable Families of Itemsets
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    Chapter 32 Transferring Instances for Model-Based Reinforcement Learning
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    Chapter 33 A Simple Model for Sequences of Relational State Descriptions
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    Chapter 34 Semi-Supervised Boosting for Multi-Class Classification
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    Chapter 35 A Joint Segmenting and Labeling Approach for Chinese Lexical Analysis
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    Chapter 36 Transferred Dimensionality Reduction
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    Chapter 37 Multiple Manifolds Learning Framework Based on Hierarchical Mixture Density Model
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    Chapter 38 Estimating Sales Opportunity Using Similarity-Based Methods
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    Chapter 39 Learning MDP Action Models Via Discrete Mixture Trees
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    Chapter 40 Continuous Time Bayesian Networks for Host Level Network Intrusion Detection
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    Chapter 41 Data Streaming with Affinity Propagation
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    Chapter 42 Semi-supervised Discriminant Analysis Via CCCP
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    Chapter 43 A Visualization-Based Exploratory Technique for Classifier Comparison with Respect to Multiple Metrics and Multiple Domains
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    Chapter 44 Pleiades: Subspace Clustering and Evaluation
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    Chapter 45 SEDiL: Software for Edit Distance Learning
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    Chapter 46 Monitoring Patterns through an Integrated Management and Mining Tool
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    Chapter 47 A Knowledge-Based Digital Dashboard for Higher Learning Institutions
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    Chapter 48 SINDBAD and SiQL: An Inductive Database and Query Language in the Relational Model
Attention for Chapter 16: State-Dependent Exploration for Policy Gradient Methods
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

1 patent


3 Dimensions

Readers on

114 Mendeley
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Chapter title
State-Dependent Exploration for Policy Gradient Methods
Chapter number 16
Book title
Machine Learning and Knowledge Discovery in Databases
Published in
Lecture notes in computer science, January 2008
DOI 10.1007/978-3-540-87481-2_16
Book ISBNs
978-3-54-087480-5, 978-3-54-087481-2

Thomas Rückstieß, Martin Felder, Jürgen Schmidhuber


Walter Daelemans, Bart Goethals, Katharina Morik

Mendeley readers

The data shown below were compiled from readership statistics for 114 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Italy 2 2%
Australia 1 <1%
Ireland 1 <1%
Netherlands 1 <1%
France 1 <1%
United Kingdom 1 <1%
New Zealand 1 <1%
Belgium 1 <1%
Other 3 3%
Unknown 100 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 40 35%
Student > Master 20 18%
Researcher 14 12%
Student > Bachelor 9 8%
Student > Doctoral Student 7 6%
Other 14 12%
Unknown 10 9%
Readers by discipline Count As %
Computer Science 66 58%
Engineering 27 24%
Economics, Econometrics and Finance 2 2%
Neuroscience 2 2%
Psychology 1 <1%
Other 3 3%
Unknown 13 11%

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 November 2018.
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Altmetric has tracked 14,788,347 research outputs across all sources so far. This one is in the 49th percentile – i.e., 49% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,490 research outputs from this source. They receive a mean Attention Score of 4.5. This one has gotten more attention than average, scoring higher than 58% 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 266,108 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 62% of its contemporaries.
We're also able to compare this research output to 128 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 58% of its contemporaries.