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Machine Learning: ECML 2004

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Cover of 'Machine Learning: ECML 2004'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Random Matrices in Data Analysis
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    Chapter 2 Data Privacy
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    Chapter 3 Breaking Through the Syntax Barrier: Searching with Entities and Relations
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    Chapter 4 Real-World Learning with Markov Logic Networks
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    Chapter 5 Strength in Diversity: The Advance of Data Analysis
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    Chapter 6 Filtered Reinforcement Learning
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    Chapter 7 Applying Support Vector Machines to Imbalanced Datasets
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    Chapter 8 Sensitivity Analysis of the Result in Binary Decision Trees
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    Chapter 9 A Boosting Approach to Multiple Instance Learning
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    Chapter 10 An Experimental Study of Different Approaches to Reinforcement Learning in Common Interest Stochastic Games
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    Chapter 11 Learning from Message Pairs for Automatic Email Answering
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    Chapter 12 Concept Formation in Expressive Description Logics
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    Chapter 13 Multi-level Boundary Classification for Information Extraction
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    Chapter 14 An Analysis of Stopping and Filtering Criteria for Rule Learning
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    Chapter 15 Adaptive Online Time Allocation to Search Algorithms
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    Chapter 16 Model Approximation for HEXQ Hierarchical Reinforcement Learning
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    Chapter 17 Iterative Ensemble Classification for Relational Data: A Case Study of Semantic Web Services
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    Chapter 18 Analyzing Multi-agent Reinforcement Learning Using Evolutionary Dynamics
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    Chapter 19 Experiments in Value Function Approximation with Sparse Support Vector Regression
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    Chapter 20 Constructive Induction for Classifying Time Series
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    Chapter 21 Fisher Kernels for Logical Sequences
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    Chapter 22 The Enron Corpus: A New Dataset for Email Classification Research
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    Chapter 23 Margin Maximizing Discriminant Analysis
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    Chapter 24 Multi-objective Classification with Info-Fuzzy Networks
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    Chapter 25 Improving Progressive Sampling via Meta-learning on Learning Curves
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    Chapter 26 Methods for Rule Conflict Resolution
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    Chapter 27 An Efficient Method to Estimate Labelled Sample Size for Transductive LDA(QDA/MDA) Based on Bayes Risk
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    Chapter 28 Analyzing Sensory Data Using Non-linear Preference Learning with Feature Subset Selection
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    Chapter 29 Dynamic Asset Allocation Exploiting Predictors in Reinforcement Learning Framework
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    Chapter 30 Justification-Based Selection of Training Examples for Case Base Reduction
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    Chapter 31 Using Feature Conjunctions Across Examples for Learning Pairwise Classifiers
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    Chapter 32 Feature Selection Filters Based on the Permutation Test
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    Chapter 33 Sparse Distributed Memories for On-Line Value-Based Reinforcement Learning
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    Chapter 34 Improving Random Forests
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    Chapter 35 The Principal Components Analysis of a Graph, and Its Relationships to Spectral Clustering
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    Chapter 36 Using String Kernels to Identify Famous Performers from Their Playing Style
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    Chapter 37 Associative Clustering
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    Chapter 38 Learning to Fly Simple and Robust
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    Chapter 39 Bayesian Network Methods for Traffic Flow Forecasting with Incomplete Data
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    Chapter 40 Matching Model Versus Single Model: A Study of the Requirement to Match Class Distribution Using Decision Trees
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    Chapter 41 Inducing Polynomial Equations for Regression
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    Chapter 42 Efficient Hyperkernel Learning Using Second-Order Cone Programming
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    Chapter 43 Effective Voting of Heterogeneous Classifiers
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    Chapter 44 Convergence and Divergence in Standard and Averaging Reinforcement Learning
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    Chapter 45 Document Representation for One-Class SVM
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    Chapter 46 Naive Bayesian Classifiers for Ranking
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    Chapter 47 Conditional Independence Trees
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    Chapter 48 Exploiting Unlabeled Data in Content-Based Image Retrieval
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    Chapter 49 Population Diversity in Permutation-Based Genetic Algorithm
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    Chapter 50 Simultaneous Concept Learning of Fuzzy Rules
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    Chapter 51 SWITCH: A Novel Approach to Ensemble Learning for Heterogeneous Data
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    Chapter 52 Estimating Attributed Central Orders
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    Chapter 53 Batch Reinforcement Learning with State Importance
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    Chapter 54 Explicit Local Models: Towards “Optimal” Optimization Algorithms
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    Chapter 55 An Intelligent Model for the Signorini Contact Problem in Belt Grinding Processes
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    Chapter 56 Cluster-Grouping: From Subgroup Discovery to Clustering
Overall attention for this book and its chapters
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Title
Machine Learning: ECML 2004
Published by
Springer Berlin Heidelberg, January 2004
DOI 10.1007/b100702
ISBNs
978-3-54-023105-9, 978-3-54-030115-8
Editors

Jean-François Boulicaut, Floriana Esposito, Fosca Giannotti, Dino Pedreschi

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 116 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Malaysia 1 <1%
Malta 1 <1%
Unknown 114 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 3%
Student > Bachelor 3 3%
Professor 1 <1%
Student > Master 1 <1%
Unknown 107 92%
Readers by discipline Count As %
Computer Science 5 4%
Biochemistry, Genetics and Molecular Biology 1 <1%
Mathematics 1 <1%
Medicine and Dentistry 1 <1%
Engineering 1 <1%
Other 0 0%
Unknown 107 92%