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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 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 473 pages, height x width: 235x155 mm, 118 Illustrations, color; 23 Illustrations, black and white; XXX, 473 p. 141 illus., 118 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Artificial Intelligence 15875
  • Izdošanas datums: 20-Jun-2025
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 9819682940
  • ISBN-13: 9789819682942
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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 VIPalielināt
  • Formāts: Paperback / softback, 473 pages, height x width: 235x155 mm, 118 Illustrations, color; 23 Illustrations, black and white; XXX, 473 p. 141 illus., 118 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Artificial Intelligence 15875
  • Izdošanas datums: 20-Jun-2025
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 9819682940
  • ISBN-13: 9789819682942
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9789819682942.html
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 1013, 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.