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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

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    Book Overview
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    Chapter 1 AUDIO : An Integrity $\underline{Audi}$ ting Framework of $\underline{O}$ utlier-Mining-as-a-Service Systems
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    Chapter 2 Differentially Private Projected Histograms: Construction and Use for Prediction
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    Chapter 3 Fairness-Aware Classifier with Prejudice Remover Regularizer
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    Chapter 4 A Live Comparison of Methods for Personalized Article Recommendation at Forbes.com
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    Chapter 5 Fast ALS-Based Tensor Factorization for Context-Aware Recommendation from Implicit Feedback
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    Chapter 6 Probability Estimation for Multi-class Classification Based on Label Ranking
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    Chapter 7 Adaptive Planning for Markov Decision Processes with Uncertain Transition Models via Incremental Feature Dependency Discovery
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    Chapter 8 APRIL: Active Preference Learning-Based Reinforcement Learning
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    Chapter 9 Autonomous Data-Driven Decision-Making in Smart Electricity Markets
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    Chapter 10 Bayesian Nonparametric Inverse Reinforcement Learning
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    Chapter 11 Bootstrapping Monte Carlo Tree Search with an Imperfect Heuristic
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    Chapter 12 Fast Reinforcement Learning with Large Action Sets Using Error-Correcting Output Codes for MDP Factorization
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    Chapter 13 Learning Policies for Battery Usage Optimization in Electric Vehicles
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    Chapter 14 Policy Iteration Based on a Learned Transition Model
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    Chapter 15 Structured Apprenticeship Learning
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    Chapter 16 A Bayesian Approach for Classification Rule Mining in Quantitative Databases
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    Chapter 17 A Bayesian Scoring Technique for Mining Predictive and Non-Spurious Rules
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    Chapter 18 Generic Pattern Trees for Exhaustive Exceptional Model Mining
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    Chapter 19 Bidirectional Semi-supervised Learning with Graphs
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    Chapter 20 Coupled Bayesian Sets Algorithm for Semi-supervised Learning and Information Extraction
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    Chapter 21 Graph-Based Transduction with Confidence
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    Chapter 22 Maximum Consistency Preferential Random Walks
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    Chapter 23 Semi-supervised Multi-label Classification
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    Chapter 24 MDL-Based Analysis of Time Series at Multiple Time-Scales
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    Chapter 25 Separable Approximate Optimization of Support Vector Machines for Distributed Sensing
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    Chapter 26 Unsupervised Inference of Auditory Attention from Biosensors
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    Chapter 27 A Family of Feed-Forward Models for Protein Sequence Classification
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    Chapter 28 General Algorithms for Mining Closed Flexible Patterns under Various Equivalence Relations
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    Chapter 29 Size Matters: Finding the Most Informative Set of Window Lengths
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    Chapter 30 Discovering Links among Social Networks
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    Chapter 31 Efficient Bi-objective Team Formation in Social Networks
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    Chapter 32 Feature-Enhanced Probabilistic Models for Diffusion Network Inference
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    Chapter 33 Influence Spread in Large-Scale Social Networks – A Belief Propagation Approach
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    Chapter 34 Location Affiliation Networks: Bonding Social and Spatial Information
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    Chapter 35 On Approximation of Real-World Influence Spread
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    Chapter 36 Opinion Formation by Voter Model with Temporal Decay Dynamics
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    Chapter 37 Viral Marketing for Product Cross-Sell through Social Networks
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    Chapter 38 Which Topic Will You Follow?
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    Chapter 39 Inferring Geographic Coincidence in Ephemeral Social Networks
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    Chapter 40 Pedestrian Quantity Estimation with Trajectory Patterns
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    Chapter 41 Socioscope: Spatio-temporal Signal Recovery from Social Media
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    Chapter 42 A Framework for Evaluating the Smoothness of Data-Mining Results
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    Chapter 43 Active Evaluation of Ranking Functions Based on Graded Relevance
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    Chapter 44 Community Trend Outlier Detection Using Soft Temporal Pattern Mining
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    Chapter 45 Data Structures for Detecting Rare Variations in Time Series
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    Chapter 46 Invariant Time-Series Classification
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    Chapter 47 Learning Bi-clustered Vector Autoregressive Models
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    Chapter 48 Discriminative Factor Alignment across Heterogeneous Feature Space
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    Chapter 49 Learning to Perceive Two-Dimensional Displays Using Probabilistic Grammars
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    Chapter 50 Transfer Spectral Clustering
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    Chapter 51 An Aspect-Lexicon Creation and Evaluation Tool for Sentiment Analysis Researchers
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    Chapter 52 Association Rule Mining Following the Web Search Paradigm
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    Chapter 53 ASV Monitor: Creating Comparability of Machine Learning Methods for Content Analysis
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    Chapter 54 ClowdFlows: A Cloud Based Scientific Workflow Platform
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    Chapter 55 Extracting Trajectories through an Efficient and Unifying Spatio-temporal Pattern Mining System
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    Chapter 56 Knowledge Discovery through Symbolic Regression with HeuristicLab
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    Chapter 57 OutRules : A Framework for Outlier Descriptions in Multiple Context Spaces
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    Chapter 58 Scientific Workflow Management with ADAMS
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    Chapter 59 TopicExplorer: Exploring Document Collections with Topic Models
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    Chapter 60 VIKAMINE – Open-Source Subgroup Discovery, Pattern Mining, and Analytics
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    Chapter 61 Learning Submodular Functions
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    Chapter 62 Matrix Factorization as Search
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    Chapter 63 Metal Binding in Proteins: Machine Learning Complements X-Ray Absorption Spectroscopy
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    Chapter 64 Modelling Input Varying Correlations between Multiple Responses
Attention for Chapter 3: Fairness-Aware Classifier with Prejudice Remover Regularizer
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Chapter title
Fairness-Aware Classifier with Prejudice Remover Regularizer
Chapter number 3
Book title
Machine Learning and Knowledge Discovery in Databases
Published by
Springer, Berlin, Heidelberg, September 2012
DOI 10.1007/978-3-642-33486-3_3
Book ISBNs
978-3-64-233485-6, 978-3-64-233486-3
Authors

Toshihiro Kamishima, Shotaro Akaho, Hideki Asoh, Jun Sakuma, Kamishima, Toshihiro, Akaho, Shotaro, Asoh, Hideki, Sakuma, Jun

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 274 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 274 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 55 20%
Student > Master 48 18%
Researcher 27 10%
Student > Bachelor 24 9%
Student > Doctoral Student 11 4%
Other 23 8%
Unknown 86 31%
Readers by discipline Count As %
Computer Science 92 34%
Social Sciences 17 6%
Engineering 15 5%
Economics, Econometrics and Finance 10 4%
Business, Management and Accounting 9 3%
Other 37 14%
Unknown 94 34%