Machine Learning and Knowledge Discovery in Databases

Table of Contents

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   Book Overview
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   Chapter 1 Maximum Margin Separations in Finite Closure Systems
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   Chapter 2 Discovering Outstanding Subgroup Lists for Numeric Targets Using MDL
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   Chapter 3 A Relaxation-Based Approach for Mining Diverse Closed Patterns
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   Chapter 4 OMBA: User-Guided Product Representations for Online Market Basket Analysis
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   Chapter 5 Online Binary Incomplete Multi-view Clustering
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   Chapter 6 Utilizing Structure-Rich Features to Improve Clustering
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   Chapter 7 Simple, Scalable, and Stable Variational Deep Clustering
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   Chapter 8 Gauss Shift: Density Attractor Clustering Faster Than Mean Shift
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    Chapter 9 Privacy-Preserving Decision Trees Training and Prediction
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    Chapter 10 Poisoning Attacks on Algorithmic Fairness
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    Chapter 11 SpecGreedy: Unified Dense Subgraph Detection
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    Chapter 12 Networked Point Process Models Under the Lens of Scrutiny
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    Chapter 13 FB2vec: A Novel Representation Learning Model for Forwarding Behaviors on Online Social Networks
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    Chapter 14 A Framework for Deep Quantification Learning
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    Chapter 15 PROMO for Interpretable Personalized Social Emotion Mining
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    Chapter 16 Progressive Supervision for Node Classification
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    Chapter 17 Modeling Dynamic Heterogeneous Network for Link Prediction Using Hierarchical Attention with Temporal RNN
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    Chapter 18 GIKT: A Graph-Based Interaction Model for Knowledge Tracing
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    Chapter 19 Simple and Effective Graph Autoencoders with One-Hop Linear Models
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    Chapter 20 Sparse Separable Nonnegative Matrix Factorization
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    Chapter 21 Robust Domain Adaptation: Representations, Weights and Inductive Bias
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    Chapter 22 Target to Source Coordinate-Wise Adaptation of Pre-trained Models
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    Chapter 23 Unsupervised Multi-source Domain Adaptation for Regression
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    Chapter 24 Open Set Domain Adaptation Using Optimal Transport
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    Chapter 25 Revisiting Wedge Sampling for Budgeted Maximum Inner Product Search
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    Chapter 26 Modeling Winner-Take-All Competition in Sparse Binary Projections
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    Chapter 27 LOAD: LSH-Based $$\ell _0$$ ℓ 0 -Sampling over Stream Data with Near-Duplicates
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    Chapter 28 Spatio-Temporal Tensor Sketching via Adaptive Sampling
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    Chapter 29 Orthogonal Mixture of Hidden Markov Models
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    Chapter 30 Poisson Graphical Granger Causality by Minimum Message Length
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    Chapter 31 Counterfactual Propagation for Semi-supervised Individual Treatment Effect Estimation
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    Chapter 32 Real-Time Fine-Grained Freeway Traffic State Estimation Under Sparse Observation
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    Chapter 33 Revisiting Convolutional Neural Networks for Citywide Crowd Flow Analytics
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    Chapter 34 RLTS: Robust Learning Time-Series Shapelets
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    Chapter 35 Disentangled Sticky Hierarchical Dirichlet Process Hidden Markov Model
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    Chapter 36 Predicting Future Classifiers for Evolving Non-linear Decision Boundaries
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    Chapter 37 Parameterless Semi-supervised Anomaly Detection in Univariate Time Series
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    Chapter 38 The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classification
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    Chapter 39 Incremental Training of a Recurrent Neural Network Exploiting a Multi-scale Dynamic Memory
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    Chapter 40 Flexible Recurrent Neural Networks
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    Chapter 41 Z-Embedding: A Spectral Representation of Event Intervals for Efficient Clustering and Classification
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    Chapter 42 Neural Cross-Domain Collaborative Filtering with Shared Entities
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    Chapter 43 NoisyCUR: An Algorithm for Two-Cost Budgeted Matrix Completion