Advances in Machine Learning

Table of Contents

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   Book Overview
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   Chapter 1 Machine Learning and Ecosystem Informatics: Challenges and Opportunities
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   Chapter 2 Density Ratio Estimation: A New Versatile Tool for Machine Learning
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   Chapter 3 Transfer Learning beyond Text Classification
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   Chapter 4 Improving Adaptive Bagging Methods for Evolving Data Streams
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   Chapter 5 Advances in Machine Learning
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   Chapter 6 Estimating Likelihoods for Topic Models
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   Chapter 7 Advances in Machine Learning
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   Chapter 8 Linear Time Model Selection for Mixture of Heterogeneous Components
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    Chapter 9 Max-margin Multiple-Instance Learning via Semidefinite Programming
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    Chapter 10 A Reformulation of Support Vector Machines for General Confidence Functions
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    Chapter 11 Robust Discriminant Analysis Based on Nonparametric Maximum Entropy
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    Chapter 12 Context-Aware Online Commercial Intention Detection
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    Chapter 13 Feature Selection via Maximizing Neighborhood Soft Margin
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    Chapter 14 Accurate Probabilistic Error Bound for Eigenvalues of Kernel Matrix
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    Chapter 15 Community Detection on Weighted Networks: A Variational Bayesian Method
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    Chapter 16 Averaged Naive Bayes Trees: A New Extension of AODE
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    Chapter 17 Automatic Choice of Control Measurements
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    Chapter 18 Coupled Metric Learning for Face Recognition with Degraded Images
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    Chapter 19 Cost-Sensitive Boosting: Fitting an Additive Asymmetric Logistic Regression Model
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    Chapter 20 On Compressibility and Acceleration of Orthogonal NMF for POMDP Compression
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    Chapter 21 Building a Decision Cluster Forest Model to Classify High Dimensional Data with Multi-classes
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    Chapter 22 Query Selection via Weighted Entropy in Graph-Based Semi-supervised Classification
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    Chapter 23 Learning Algorithms for Domain Adaptation
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    Chapter 24 Mining Multi-label Concept-Drifting Data Streams Using Dynamic Classifier Ensemble
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    Chapter 25 Learning Continuous-Time Information Diffusion Model for Social Behavioral Data Analysis
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    Chapter 26 Privacy-Preserving Evaluation of Generalization Error and Its Application to Model and Attribute Selection
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    Chapter 27 Coping with Distribution Change in the Same Domain Using Similarity-Based Instance Weighting
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    Chapter 28 Monte-Carlo Tree Search in Poker Using Expected Reward Distributions
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    Chapter 29 Injecting Structured Data to Generative Topic Model in Enterprise Settings
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    Chapter 30 Weighted Nonnegative Matrix Co-Tri-Factorization for Collaborative Prediction