Machine Learning and Knowledge Discovery in Databases

Table of Contents

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   Book Overview
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   Chapter 1 Bayesian Knowledge Corroboration with Logical Rules and User Feedback
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   Chapter 2 Learning an Affine Transformation for Non-linear Dimensionality Reduction
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   Chapter 3 NDPMine: Efficiently Mining Discriminative Numerical Features for Pattern-Based Classification
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   Chapter 4 Hidden Conditional Ordinal Random Fields for Sequence Classification
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   Chapter 5 A Unifying View of Multiple Kernel Learning
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   Chapter 6 Evolutionary Dynamics of Regret Minimization
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   Chapter 7 Recognition of Instrument Timbres in Real Polytimbral Audio Recordings
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   Chapter 8 Finding Critical Nodes for Inhibiting Diffusion of Complex Contagions in Social Networks
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    Chapter 9 Semi-supervised Abstraction-Augmented String Kernel for Multi-level Bio-Relation Extraction
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    Chapter 10 Online Knowledge-Based Support Vector Machines
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    Chapter 11 Learning with Randomized Majority Votes
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    Chapter 12 Exploration in Relational Worlds
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    Chapter 13 Efficient Confident Search in Large Review Corpora
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    Chapter 14 Learning to Tag from Open Vocabulary Labels
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    Chapter 15 A Robustness Measure of Association Rules
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    Chapter 16 Automatic Model Adaptation for Complex Structured Domains
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    Chapter 17 Collective Traffic Forecasting
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    Chapter 18 On Detecting Clustered Anomalies Using SCiForest
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    Chapter 19 Constrained Parameter Estimation for Semi-supervised Learning: The Case of the Nearest Mean Classifier
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    Chapter 20 Online Learning in Adversarial Lipschitz Environments
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    Chapter 21 Summarising Data by Clustering Items
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    Chapter 22 Classification and Novel Class Detection of Data Streams in a Dynamic Feature Space
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    Chapter 23 Latent Structure Pattern Mining
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    Chapter 24 First-Order Bayes-Ball
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    Chapter 25 Learning from Demonstration Using MDP Induced Metrics
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    Chapter 26 Demand-Driven Tag Recommendation
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    Chapter 27 Solving Structured Sparsity Regularization with Proximal Methods
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    Chapter 28 Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models
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    Chapter 29 Improved MinMax Cut Graph Clustering with Nonnegative Relaxation
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    Chapter 30 Integrating Constraint Programming and Itemset Mining
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    Chapter 31 Topic Modeling for Personalized Recommendation of Volatile Items
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    Chapter 32 Conditional Ranking on Relational Data