Advances in Knowledge Discovery and Data Mining

Table of Contents

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   Book Overview
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   Chapter 1 Neural Additive and Basis Models with Feature Selection and Interactions
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   Chapter 2 Random Mask Perturbation Based Explainable Method of Graph Neural Networks
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   Chapter 3 RouteExplainer: An Explanation Framework for Vehicle Routing Problem
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   Chapter 4 On the Efficient Explanation of Outlier Detection Ensembles Through Shapley Values
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   Chapter 5 Interpreting Pretrained Language Models via Concept Bottlenecks
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   Chapter 6 Unmasking Dementia Detection by Masking Input Gradients: A JSM Approach to Model Interpretability and Precision
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   Chapter 7 Towards Nonparametric Topological Layers in Neural Networks
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   Chapter 8 Streaming Fair k -Center Clustering over Massive Dataset with Performance Guarantee
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    Chapter 9 Projection-Free Bandit Convex Optimization over Strongly Convex Sets
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    Chapter 10 Adaptive Prediction Interval for Data Stream Regression
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    Chapter 11 Probabilistic Guarantees of Stochastic Recursive Gradient in Non-convex Finite Sum Problems
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    Chapter 12 Rethinking Personalized Federated Learning with Clustering-Based Dynamic Graph Propagation
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    Chapter 13 Unveiling Backdoor Risks Brought by Foundation Models in Heterogeneous Federated Learning
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    Chapter 14 Combating Quality Distortion in Federated Learning with Collaborative Data Selection
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    Chapter 15 Neural Marked Hawkes Process for Limit Order Book Modeling
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    Chapter 16 How Large Corpora Sizes Influence the Distribution of Low Frequency Text n -grams
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    Chapter 17 Meta-Reinforcement Learning Algorithm Based on Reward and Dynamic Inference
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    Chapter 18 SecureBoost $$+$$ + : Large Scale and High-Performance Vertical Federated Gradient Boosting Decision Tree
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    Chapter 19 Construct a Secure CNN Against Gradient Inversion Attack
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    Chapter 20 Backdoor Attack Against One-Class Sequential Anomaly Detection Models
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    Chapter 21 DALLMi : Domain Adaption for LLM-Based Multi-label Classifier
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    Chapter 22 Contrastive Learning for Unsupervised Sentence Embedding with False Negative Calibration
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    Chapter 23 Recovering Population Dynamics from a Single Point Cloud Snapshot
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    Chapter 24 SAWTab: Smoothed Adaptive Weighting for Tabular Data in Semi-supervised Learning
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    Chapter 25 Improving Anti-money Laundering via Fourier-Based Contrastive Learning
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    Chapter 26 A Novel SegNet Model for Crack Image Semantic Segmentation in Bridge Inspection
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    Chapter 27 Graph-based Dynamic Preference Modeling for Personalized Recommendation
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    Chapter 28 LEAF: A Less Expert Annotation Framework with Active Learning
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    Chapter 29 MLT-Trans: Multi-level Token Transformer for Hierarchical Image Classification
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    Chapter 30 Improving Knowledge Tracing via Considering Students’ Interaction Patterns
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    Chapter 31 MDAN: Multi-distribution Adaptive Networks for LTV Prediction