Produktbild: Advances in Knowledge Discovery and Data Mining
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Advances in Knowledge Discovery and Data Mining 30th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2026, Hong Kong, China, June 9–12, 2026, Proceedings, Part III

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

15.07.2026

Abbildungen

XLIII, 186 illus., 169 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen

Herausgeber

Raymond Chi-Wing Wong + weitere

Verlag

Springer Singapore

Seitenzahl

589

Maße (L/B)

23,5/15,5 cm

Sprache

Englisch

ISBN

978-981-9214-64-8

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

15.07.2026

Abbildungen

XLIII, 186 illus., 169 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen

Herausgeber

Verlag

Springer Singapore

Seitenzahl

589

Maße (L/B)

23,5/15,5 cm

Sprache

Englisch

ISBN

978-981-9214-64-8

Herstelleradresse

Springer Nature Customer Service Center GmbH
Europaplatz 3
69115 Heidelberg
DE
[email protected]

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  • Produktbild: Advances in Knowledge Discovery and Data Mining
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    .- VCDF: A Validated Consensus-Driven Framework for Time Series Causal Discovery.

    .- HPMixer: Hierarchical Patching for Multivariate Time Series Forecasting.

    .- Fair Shared Resource Allocation with Bounded Conflicts over Unit and Laminar Interval Graphs.

    .- Explainable Cognitive Task Classification in Pediatric EEG Using CPCC-Based Functional Connectivity Images.

    .- RouteLlama: Proactive Disentanglement for Robust Multi-Domain Text Mining.

    .- Graph Representation Learning with Laplacian Pyramid Residuals for Graph Classification.

    .- Differentiable Rendering Powered End-to-End Adversarial Attack Evaluation.

    .- Node2Graph: Diagnosing Task Unification in Graph Learning.

    .- Towards Learning Nonlinear Multivariate Correlations in Tabular Data.

    .- Hierarchical Graph-Language Models for Sequential Sentence Classification.

    .- Differentiable Zero-One Loss via Hypersimplex Projections.

    .- Efficient Inference for Flow Matching via Unified Path CFG.

    .- CAMO: Causality-Guided Adversarial Multimodal Domain Generalization for Crisis Classification.

    .- C2FFormer: Coarse-to-Fine Time Series Imputation via Autoregressive Transformer.

    .- X-MAP: eXplainable Misclassification Analysis and Profiling for Spam and Phishing Detection.

    .- ModTGCN: Modularity-aware Graph Neural Networks for Text Classification.

    .- POF-HG: Fusion of Public Opinion Field Effect and Heterogeneous Hypergraph for Information Diffusion Prediction.

    .- AEGI: Anchor Event Guided Inference for TKGQA.

    .- From Informal Descriptions to Formal MILP Models through a Multi-agent Approach with Structured Knowledge Integration.

    .- MetaGD-CAN: A Hybrid Generative–Discriminative Method for Cancer Detection in EHR Data.

    .- CSP-HEIDI - Visualising Closest Subspace Points in R^d clusters and classes.

    .- ICR-NET: Robust Deepfake Detection under Temporal Corruption.

    .- Prompt-tuning with Attribute Guidance for Low-resource Entity Matching.

    .- Graph Anomaly Detection Boundary Learning via Local and Global Structure Modeling.

    .- From Soft Logic to Hard Rules: A Differentiable Boolean Framework for Interpretable and Balanced Classification.

    .- GlassMol: Interpretable Molecular Property Prediction with Concept Bottleneck Models.

    .- Tabular-to-Image Transformation for Transfer Learning on Heterogeneous Health Data.

    .- EQCKD: Enhanced Quantization with Contrastive Knowledge Distillation for Lightweight Sequential Recommendation.

    .- Learning Multi-Aspect Item Palette: A Semantic Tokenization Framework for Generative Recommendation.

    .- SAGE: Semantic Alignment and Geometric Enhancement for Efficient Few-Shot Intent Detection.

    .- Interpretable Prediction of Alzheimer's Disease via Neural Granger Causality Discovery.

    .- Are There Any Hidden Agents in Your Recommendations? Anomaly Detection via Structure Purification and Stability Verification.

    .- SenTS: A Unified Time-Spectral Modeling Framework with Periodic Regularization for Sensing Behavior Discrimination.

    .- Physics-Guided Knowledge Graphs for Verifiable Wildfire Prediction.

    .- Conditional Contrastive Confidence-Based Uncertainty Quantification for LLMs.

    .- LLM-SATPOI: A Semantic-Aligned Large Language Model with Temporal Modeling for Next POI Recommendation.

    .- Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation.

    .- Sequence-to-Image Transformation for Sequence Classification Using Rips Complex Construction and Chaos Game Representation.

    .- Graph-Based Diffusion Enables Interface-Aware Sequence–Structure Co-Design of Protein Complexes.

    .- PallasGNN: Curriculum-Based Pattern Mining for Robust GNNs.

    .- TabCL: Continual Malware Classification with Tabular-Aware Generation.

    .- Class Conditioned Gaussian Mixture Modeling for Imbalanced Time Series Quantification.

    .- A Path Value-aware Reinforcement Learning method for Knowledge Graph Question Answering.