Machine Learning and Knowledge Discovery in Databases

Table of Contents

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   Book Overview
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   Chapter 1 BoostMF: Boosted Matrix Factorisation for Collaborative Ranking
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   Chapter 2 Convex Factorization Machines
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   Chapter 3 Generalized Matrix Factorizations as a Unifying Framework for Pattern Set Mining: Complexity Beyond Blocks
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   Chapter 4 Scalable Bayesian Non-negative Tensor Factorization for Massive Count Data
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   Chapter 5 A Practical Approach to Reduce the Learning Bias Under Covariate Shift
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   Chapter 6 Hyperparameter Optimization with Factorized Multilayer Perceptrons
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   Chapter 7 Hyperparameter Search Space Pruning – A New Component for Sequential Model-Based Hyperparameter Optimization
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   Chapter 8 Multi-Task Learning with Group-Specific Feature Space Sharing
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    Chapter 9 Opening the Black Box: Revealing Interpretable Sequence Motifs in Kernel-Based Learning Algorithms
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    Chapter 10 Fast Generation of Best Interval Patterns for Nonmonotonic Constraints
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    Chapter 11 Non-parametric Jensen-Shannon Divergence
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    Chapter 12 Swap Randomization of Bases of Sequences for Mining Satellite Image Times Series
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    Chapter 13 The Difference and the Norm — Characterising Similarities and Differences Between Databases
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    Chapter 14 Dyad Ranking Using A Bilinear Plackett-Luce Model
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    Chapter 15 Fast Training of Support Vector Machines for Survival Analysis
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    Chapter 16 Superset Learning Based on Generalized Loss Minimization
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    Chapter 17 Bayesian Modelling of the Temporal Aspects of Smart Home Activity with Circular Statistics
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    Chapter 18 Message Scheduling Methods for Belief Propagation
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    Chapter 19 Output-Sensitive Adaptive Metropolis-Hastings for Probabilistic Programs
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    Chapter 20 Planning in Discrete and Continuous Markov Decision Processes by Probabilistic Programming
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    Chapter 21 Simplifying, Regularizing and Strengthening Sum-Product Network Structure Learning
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    Chapter 22 Sparse Bayesian Recurrent Neural Networks
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    Chapter 23 Structured Prediction of Sequences and Trees Using Infinite Contexts
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    Chapter 24 Temporally Coherent Role-Topic Models (TCRTM): Deinterlacing Overlapping Activity Patterns
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    Chapter 25 The Blind Leading the Blind: Network-Based Location Estimation Under Uncertainty
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    Chapter 26 Weighted Rank Correlation: A Flexible Approach Based on Fuzzy Order Relations
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    Chapter 27 Concurrent Inference of Topic Models and Distributed Vector Representations
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    Chapter 28 Differentially Private Analysis of Outliers
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    Chapter 29 Inferring Unusual Crowd Events from Mobile Phone Call Detail Records
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    Chapter 30 Learning Pretopological Spaces for Lexical Taxonomy Acquisition
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    Chapter 31 Multidimensional Prediction Models When the Resolution Context Changes
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    Chapter 32 Semi-supervised Subspace Co-Projection for Multi-class Heterogeneous Domain Adaptation
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    Chapter 33 Towards Computation of Novel Ideas from Corpora of Scientific Text
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    Chapter 34 Discovering Audience Groups and Group-Specific Influencers
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    Chapter 35 Estimating Potential Customers Anywhere and Anytime Based on Location-Based Social Networks
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    Chapter 36 Exact Hybrid Covariance Thresholding for Joint Graphical Lasso
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    Chapter 37 Fast Inbound Top-K Query for Random Walk with Restart
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    Chapter 38 Finding Community Topics and Membership in Graphs
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    Chapter 39 Finding Dense Subgraphs in Relational Graphs
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    Chapter 40 Generalized Modularity for Community Detection
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    Chapter 41 Handling Oversampling in Dynamic Networks Using Link Prediction
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    Chapter 42 Hierarchical Sparse Dictionary Learning
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    Chapter 43 Latent Factors Meet Homophily in Diffusion Modelling
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    Chapter 44 Maintaining Sliding-Window Neighborhood Profiles in Interaction Networks
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    Chapter 45 Response-Guided Community Detection: Application to Climate Index Discovery
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    Chapter 46 Robust Classification of Information Networks by Consistent Graph Learning