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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

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    Book Overview
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    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 39: Learning MDP Action Models Via Discrete Mixture Trees
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Chapter title
Learning MDP Action Models Via Discrete Mixture Trees
Chapter number 39
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_39
Book ISBNs
978-3-54-087480-5, 978-3-54-087481-2
Authors

Michael Wynkoop, Thomas Dietterich

Editors

Walter Daelemans, Bart Goethals, Katharina Morik

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Russia 1 11%
Belgium 1 11%
Unknown 7 78%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 33%
Other 2 22%
Professor > Associate Professor 2 22%
Researcher 1 11%
Professor 1 11%
Other 0 0%
Readers by discipline Count As %
Computer Science 9 100%