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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
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    Chapter 1 BeatLex: Summarizing and Forecasting Time Series with Patterns
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    Chapter 2 Behavioral Constraint Template-Based Sequence Classification
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    Chapter 3 Efficient Sequence Regression by Learning Linear Models in All-Subsequence Space
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    Chapter 4 Subjectively Interesting Connecting Trees
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    Chapter 5 Malware Detection by Analysing Encrypted Network Traffic with Neural Networks
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    Chapter 6 PEM: A Practical Differentially Private System for Large-Scale Cross-Institutional Data Mining
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    Chapter 7 Bayesian Heatmaps: Probabilistic Classification with Multiple Unreliable Information Sources
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    Chapter 8 Bayesian Inference for Least Squares Temporal Difference Regularization
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    Chapter 9 Discovery of Causal Models that Contain Latent Variables Through Bayesian Scoring of Independence Constraints
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    Chapter 10 Labeled DBN Learning with Community Structure Knowledge
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    Chapter 11 Multi-view Generative Adversarial Networks
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    Chapter 12 Online Sparse Collapsed Hybrid Variational-Gibbs Algorithm for Hierarchical Dirichlet Process Topic Models
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    Chapter 13 PAC-Bayesian Analysis for a Two-Step Hierarchical Multiview Learning Approach
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    Chapter 14 Partial Device Fingerprints
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    Chapter 15 Robust Multi-view Topic Modeling by Incorporating Detecting Anomalies
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    Chapter 16 A Regularization Method with Inference of Trust and Distrust in Recommender Systems
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    Chapter 17 A Unified Contextual Bandit Framework for Long- and Short-Term Recommendations
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    Chapter 18 Perceiving the Next Choice with Comprehensive Transaction Embeddings for Online Recommendation
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    Chapter 19 Adaptive Skip-Train Structured Regression for Temporal Networks
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    Chapter 20 ALADIN: A New Approach for Drug–Target Interaction Prediction
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    Chapter 21 Co-Regularised Support Vector Regression
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    Chapter 22 Online Regression with Controlled Label Noise Rate
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    Chapter 23 Generalized Inverse Reinforcement Learning with Linearly Solvable MDP
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    Chapter 24 Max K-Armed Bandit: On the ExtremeHunter Algorithm and Beyond
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    Chapter 25 Variational Thompson Sampling for Relational Recurrent Bandits
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    Chapter 26 Explaining Deviating Subsets Through Explanation Networks
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    Chapter 27 Flash Points: Discovering Exceptional Pairwise Behaviors in Vote or Rating Data
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    Chapter 28 A Multiscale Bezier-Representation for Time Series that Supports Elastic Matching
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    Chapter 29 Arbitrated Ensemble for Time Series Forecasting
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    Chapter 30 Cost Sensitive Time-Series Classification
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    Chapter 31 Cost-Sensitive Perceptron Decision Trees for Imbalanced Drifting Data Streams
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    Chapter 32 Efficient Temporal Kernels Between Feature Sets for Time Series Classification
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    Chapter 33 Forecasting and Granger Modelling with Non-linear Dynamical Dependencies
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    Chapter 34 Learning TSK Fuzzy Rules from Data Streams
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    Chapter 35 Non-parametric Online AUC Maximization
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    Chapter 36 On-Line Dynamic Time Warping for Streaming Time Series
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    Chapter 37 PowerCast: Mining and Forecasting Power Grid Sequences
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    Chapter 38 UAPD: Predicting Urban Anomalies from Spatial-Temporal Data
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    Chapter 39 LKT-FM: A Novel Rating Pattern Transfer Model for Improving Non-overlapping Cross-Domain Collaborative Filtering
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    Chapter 40 Distributed Multi-task Learning for Sensor Network
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    Chapter 41 Learning Task Clusters via Sparsity Grouped Multitask Learning
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    Chapter 42 Lifelong Learning with Gaussian Processes
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    Chapter 43 Personalized Tag Recommendation for Images Using Deep Transfer Learning
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    Chapter 44 Ranking Based Multitask Learning of Scoring Functions
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    Chapter 45 Theoretical Analysis of Domain Adaptation with Optimal Transport
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    Chapter 46 TSP: Learning Task-Specific Pivots for Unsupervised Domain Adaptation
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    Chapter 47 $$k^2$$ k 2 -means for Fast and Accurate Large Scale Clustering
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    Chapter 48 A Simple Exponential Family Framework for Zero-Shot Learning
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    Chapter 49 DeepCluster: A General Clustering Framework Based on Deep Learning
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    Chapter 50 Multi-view Spectral Clustering on Conflicting Views
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    Chapter 51 Pivot-Based Distributed K-Nearest Neighbor Mining
Attention for Chapter 16: A Regularization Method with Inference of Trust and Distrust in Recommender Systems
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Chapter title
A Regularization Method with Inference of Trust and Distrust in Recommender Systems
Chapter number 16
Book title
Machine Learning and Knowledge Discovery in Databases
Published by
Springer, Cham, September 2017
DOI 10.1007/978-3-319-71246-8_16
Book ISBNs
978-3-31-971245-1, 978-3-31-971246-8
Authors

Dimitrios Rafailidis, Fabio Crestani

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 14%
Student > Doctoral Student 4 11%
Student > Postgraduate 3 8%
Student > Bachelor 2 6%
Other 2 6%
Other 6 17%
Unknown 14 39%
Readers by discipline Count As %
Computer Science 15 42%
Engineering 3 8%
Business, Management and Accounting 1 3%
Physics and Astronomy 1 3%
Arts and Humanities 1 3%
Other 0 0%
Unknown 15 42%