Data Science: Foundations and Applications

29th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2025, Sydney, NSW, Australia, June 10-13, 2025, Proceedings, Part VI

Xintao Wu, Myra Spiliopoulou, Can WANG, Vipin Kumar, Longbing Cao (Herausgeber)

Buch | Softcover

473 Seiten

2025
Springer Nature Switzerland AG (Verlag)
978-981-96-8294-2 (ISBN)

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The two-volume set LNAI 15875 + 15876 constitutes the proceedings of the 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2025 Special Session, held in Sydney, NSW, Australia, during June 10–13, 2025.

The 68 full papers included in this set were carefully reviewed and selected from 696 submissions. They were organized in topical sections as follows: survey track; machine learning; trustworthiness; learning on complex data; graph mining; machine learning applications; representation learning; scientific/business data analysis; and special track on large language models.

.- Survey Track.
.- Large Language Models for Cybersecurity Education: A Survey of Current Practices and Future Directions.
.- A Comprehensive Survey on Deep Learning Solutions for 3D Flood Mapping.
.- A Survey of Foundation Models for Environmental Science.
.- A Survey on Efficient Graph Reachability Queries.
.- Machine Learning.
.- Disentangled Representation Learning for Geospatial-temporal Data Modeling.
.- Treatment Effect Estimation for Graph-Structured Targets.
.- Dynamic DropConnect: Enhancing Neural Network Robustness through Adaptive Edge Dropping Strategies.
.- The Brownian Integral Kernel: A New Kernel for Modeling Integrated Brownian Motions.
.- Fed-ARIMA-OPARBFN: An Ensemble Model for Cross-Domain Crop Yield Time Series Prediction Based on Federated Learning.
.- S-CPD: Topological Smoothing-Based Change Point Detection.
.- VDASI: VAE-Enhanced Degradation-Aware System Identification Using Constrained Latent Spaces.
.- Disentangled Mode-Specific Representations for Tensor Time Series via Contrastive Learning.
.- PFformer: A Position-Free Transformer Variant for Extreme-Adaptive Multivariate Time Series Forecasting.
.- Advancing Long-Term High-Frequency Dissolved Oxygen Forecasting for Australian Rivers.
.- CNO-former: Chaotic Neural Oscillatory Transformer for Social Media Text Generation.
.- Multilingual Non-Factoid Question Answering with Answer Paragraph Selection
.- Turning Uncertainty to Information by Intervals in Ensemble Classifiers.
.- Determining the Need for Multi-Label Classifiers by Measuring Unexplained Covariance.
.- Evaluating Generative Vehicle Trajectory Models for Traffic Intersection Dynamics.
.- Trustworthiness.
.- Inversion Triplet - A Contrastive Backdoor Mitigation Method for Self-Supervised Vision Encoders.
.- Beyond Uniformity: Robust Backdoor Attacks on Deep Neural Networks with Trigger Selection.
.- Defence Against Multi-target Multi-trigger Backdoor Attack.
.- How to Backdoor Consistency Models?.
.- Multi-granularity Policy Explanation of Deep Reinforcement Learning Based on Saliency Map Clustering.
.- FACROC: A Fairness Measure for Fair Clustering Through ROC Curves.
.- Learning on Complex Data.
.- Action Sequence Analysis Using Temporal Commonsense Knowledge.
.- Foundation Model for Lossy Compression of Spatiotemporal Scientific Data.
.- CANTER: A Novel Causal Model for Tourism Demand Forecasting.
.- Time-Aware Complex Attention Space for Temporal Knowledge Graph Completion.
.- Adaptive Extraction of Variable-Length Subsequence Patterns in Noisy Time Series.
.- Hunting Inside N-Quantiles of Outliers (Hino).
.- Fast Approximation Algorithm for Euclidean Minimum Spanning Tree Building in High Dimensions.
.- ShuttleSHAP: A Turn-Based Feature Attribution Approach for Analyzing Forecasting Models in Badminton.
.- Offline Map Matching Based on Localization Error Distribution Modeling.

Erscheinungsdatum	13.06.2025
Reihe/Serie	Lecture Notes in Artificial Intelligence
Reihe/Serie	Lecture Notes in Computer Science
Zusatzinfo	118 Illustrations, color; 23 Illustrations, black and white
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Themenwelt	Schulbuch / Wörterbuch ► Unterrichtsvorbereitung ► Unterrichts-Handreichungen
	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
	Sozialwissenschaften ► Pädagogik
	Technik ► Elektrotechnik / Energietechnik
ISBN-10	981-96-8294-0 / 9819682940
ISBN-13	978-981-96-8294-2 / 9789819682942
Zustand	Neuware