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