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Machine Learning and Knowledge Discovery in Databases

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Cover of 'Machine Learning and Knowledge Discovery in Databases'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 FLIP: Active Learning for Relational Network Classification
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    Chapter 2 Clustering via Mode Seeking by Direct Estimation of the Gradient of a Log-Density
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    Chapter 3 Local Policy Search in a Convex Space and Conservative Policy Iteration as Boosted Policy Search
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    Chapter 4 Code You Are Happy to Paste: An Algorithmic Dictionary of Exponential Families
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    Chapter 5 Statistical Hypothesis Testing in Positive Unlabelled Data
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    Chapter 6 Students, Teachers, Exams and MOOCs: Predicting and Optimizing Attainment in Web-Based Education Using a Probabilistic Graphical Model
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    Chapter 7 Gaussian Process Multi-task Learning Using Joint Feature Selection
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    Chapter 8 Separating Rule Refinement and Rule Selection Heuristics in Inductive Rule Learning
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    Chapter 9 Scalable Information Flow Mining in Networks
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    Chapter 10 Link Prediction in Multi-modal Social Networks
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    Chapter 11 Faster Way to Agony
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    Chapter 12 Speeding Up Recovery from Concept Drifts
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    Chapter 13 Training Restricted Boltzmann Machines with Overlapping Partitions
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    Chapter 14 Integer Bayesian Network Classifiers
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    Chapter 15 Multi-target Regression via Random Linear Target Combinations
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    Chapter 16 Ratio-Based Multiple Kernel Clustering
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    Chapter 17 Evidence-Based Clustering for Scalable Inference in Markov Logic
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    Chapter 18 On Learning Matrices with Orthogonal Columns or Disjoint Supports
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    Chapter 19 Scalable Moment-Based Inference for Latent Dirichlet Allocation
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    Chapter 20 Unsupervised Feature Selection via Unified Trace Ratio Formulation and K -means Clustering (TRACK)
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    Chapter 21 On the Equivalence between Deep NADE and Generative Stochastic Networks
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    Chapter 22 Scalable Nonnegative Matrix Factorization with Block-wise Updates
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    Chapter 23 Convergence of Min-Sum-Min Message-Passing for Quadratic Optimization
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    Chapter 24 Clustering Image Search Results by Entity Disambiguation
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    Chapter 25 Accelerating Model Selection with Safe Screening for L 1 -Regularized L 2 -SVM
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    Chapter 26 Kernel Alignment Inspired Linear Discriminant Analysis
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    Chapter 27 Transfer Learning with Multiple Sources via Consensus Regularized Autoencoders
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    Chapter 28 Branty: A Social Media Ranking Tool for Brands
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    Chapter 29 MinUS : Mining User Similarity with Trajectory Patterns
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    Chapter 30 KnowNow: A Serendipity-Based Educational Tool for Learning Time-Linked Knowledge
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    Chapter 31 Khiops CoViz: A Tool for Visual Exploratory Analysis of k -Coclustering Results
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    Chapter 32 PYTHIA: Employing Lexical and Semantic Features for Sentiment Analysis
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    Chapter 33 Spá: A Web-Based Viewer for Text Mining in Evidence Based Medicine
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    Chapter 34 Propositionalization Online
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    Chapter 35 Interactive Medical Miner : Interactively Exploring Subpopulations in Epidemiological Datasets
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    Chapter 36 WebDR: A Web Workbench for Data Reduction
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    Chapter 37 GrammarViz 2.0: A Tool for Grammar-Based Pattern Discovery in Time Series
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    Chapter 38 Machine Learning and Knowledge Discovery in Databases
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    Chapter 39 BestTime: Finding Representatives in Time Series Datasets
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    Chapter 40 BMaD – A Boolean Matrix Decomposition Framework
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    Chapter 41 Analyzing and Grounding Social Interaction in Online and Offline Networks
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    Chapter 42 Be Certain of How-to before Mining Uncertain Data
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    Chapter 43 Active Learning Is Planning: Nonmyopic ε -Bayes-Optimal Active Learning of Gaussian Processes
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    Chapter 44 Generalized Online Sparse Gaussian Processes with Application to Persistent Mobile Robot Localization
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    Chapter 45 Distributional Clauses Particle Filter
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    Chapter 46 Network Reconstruction for the Identification of miRNA:mRNA Interaction Networks
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    Chapter 47 Machine Learning Approaches for Metagenomics
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    Chapter 48 Sampling-Based Data Mining Algorithms: Modern Techniques and Case Studies
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    Chapter 49 Heterogeneous Stream Processing and Crowdsourcing for Traffic Monitoring: Highlights
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    Chapter 50 Agents Teaching Agents in Reinforcement Learning (Nectar Abstract)
Attention for Chapter 14: Integer Bayesian Network Classifiers
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Citations

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Chapter title
Integer Bayesian Network Classifiers
Chapter number 14
Book title
Machine Learning and Knowledge Discovery in Databases
Published by
Springer, Berlin, Heidelberg, September 2014
DOI 10.1007/978-3-662-44845-8_14
Book ISBNs
978-3-66-244844-1, 978-3-66-244845-8
Authors

Sebastian Tschiatschek, Karin Paul, Franz Pernkopf, Tschiatschek, Sebastian, Paul, Karin, Pernkopf, Franz

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 283 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 4 1%
United States 3 1%
Germany 2 <1%
Virgin Islands, U.S. 1 <1%
Italy 1 <1%
Mexico 1 <1%
Ireland 1 <1%
China 1 <1%
United Kingdom 1 <1%
Other 0 0%
Unknown 268 95%

Demographic breakdown

Readers by professional status Count As %
Student > Master 50 18%
Student > Ph. D. Student 47 17%
Researcher 25 9%
Student > Bachelor 24 8%
Student > Doctoral Student 12 4%
Other 38 13%
Unknown 87 31%
Readers by discipline Count As %
Computer Science 90 32%
Engineering 38 13%
Agricultural and Biological Sciences 12 4%
Medicine and Dentistry 8 3%
Mathematics 8 3%
Other 34 12%
Unknown 93 33%