Machine Learning and Knowledge Discovery in Databases: Research Track

Table of Contents

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   Book Overview
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   Chapter 1 Learning Objective-Specific Active Learning Strategies with Attentive Neural Processes
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   Chapter 2 Real: A Representative Error-Driven Approach for Active Learning
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   Chapter 3 Knowledge-Driven Active Learning
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   Chapter 4 ActiveGLAE: A Benchmark for Deep Active Learning with Transformers
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   Chapter 5 DiffusAL: Coupling Active Learning with Graph Diffusion for Label-Efficient Node Classification
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   Chapter 6 Quantifying Robustness to Adversarial Word Substitutions
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   Chapter 7 Enhancing Adversarial Training via Reweighting Optimization Trajectory
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   Chapter 8 Adversarial Imitation Learning with Controllable Rewards for Text Generation
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    Chapter 9 Towards Minimising Perturbation Rate for Adversarial Machine Learning with Pruning
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    Chapter 10 Adversarial Sample Detection Through Neural Network Transport Dynamics
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    Chapter 11 CVTGAD: Simplified Transformer with Cross-View Attention for Unsupervised Graph-Level Anomaly Detection
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    Chapter 12 Graph-Level Anomaly Detection via Hierarchical Memory Networks
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    Chapter 13 Semi-supervised Learning from Active Noisy Soft Labels for Anomaly Detection
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    Chapter 14 Learning with Noisy Labels by Adaptive Gradient-Based Outlier Removal
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    Chapter 15 DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection
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    Chapter 16 Marvolo: Programmatic Data Augmentation for Deep Malware Detection
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    Chapter 17 A Transductive Forest for Anomaly Detection with Few Labels
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    Chapter 18 Co-Evolving Graph Reasoning Network for Emotion-Cause Pair Extraction
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    Chapter 19 SpotGAN: A Reverse-Transformer GAN Generates Scaffold-Constrained Molecules with Property Optimization
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    Chapter 20 Spatio-Temporal Pyramid Networks for Traffic Forecasting
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    Chapter 21 A Passage Retrieval Transformer-Based Re-Ranking Model for Truthful Consumer Health Search
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    Chapter 22 KESHEM: Knowledge Enabled Short Health Misinformation Detection Framework
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    Chapter 23 Dynamic Thresholding for Accurate Crack Segmentation Using Multi-objective Optimization
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    Chapter 24 Co-supervised Pre-training of Pocket and Ligand
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    Chapter 25 Decompose, Then Reconstruct: A Framework of Network Structures for Click-Through Rate Prediction
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    Chapter 26 DynaBench: A Benchmark Dataset for Learning Dynamical Systems from Low-Resolution Data
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    Chapter 28 Cooperative Bayesian Optimization for Imperfect Agents
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    Chapter 29 Leveraging Variational Autoencoders for Multiple Data Imputation
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    Chapter 30 A New Framework for Classifying Probability Density Functions
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    Chapter 31 Learning Conditional Instrumental Variable Representation for Causal Effect Estimation
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    Chapter 32 A KNN-Based Non-Parametric Conditional Independence Test for Mixed Data and Application in Causal Discovery
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    Chapter 33 PEACE: Cross-Platform Hate Speech Detection - A Causality-Guided Framework
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    Chapter 34 Estimating Treatment Effects Under Heterogeneous Interference
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    Chapter 35 Regularization for Uplift Regression
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    Chapter 36 Powered Dirichlet Process - Controlling the “Rich-Get-Richer” Assumption in Bayesian Clustering
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    Chapter 37 Contrastive Hierarchical Clustering
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    Chapter 38 Contrastive Learning with Cluster-Preserving Augmentation for Attributed Graph Clustering
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    Chapter 39 k-SubMix: Common Subspace Clustering on Mixed-Type Data
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    Chapter 40 Transformer-Based Contrastive Multi-view Clustering via Ensembles
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    Chapter 41 A Deep Dynamic Latent Block Model for the Co-Clustering of Zero-Inflated Data Matrices
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    Chapter 42 cuSLINK: Single-Linkage Agglomerative Clustering on the GPU
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    Chapter 43 Socially Fair Center-Based and Linear Subspace Clustering
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    Chapter 44 Visualizing Overlapping Biclusterings and Boolean Matrix Factorizations