Titlebook: Advances in Knowledge Discovery and Data Mining; 28th Pacific-Asia Co De-Nian Yang,Xing Xie,Jerry Chun-Wei Lin Conference proceedings 2024

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/a/image/148645.jpg

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https://doi.org/10.1007/978-981-97-2253-2machine learning; artificial intelligence; probability and statistics; Web mining; security and privacy;

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978-981-97-2252-5The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor

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Advances in Knowledge Discovery and Data Mining978-981-97-2253-2Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Edward H. Cooper,Geoffrey R. Gilessame labels or otherwise pushed apart. Such dispersion process in the representation space benefits the downstream classification tasks. However, when applied to regression tasks directly, such dispersion lacks guidance of the relationship among target labels (i.e. the label distances), which leads

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Liver resection for malignant disease,o determine whether an advertisement has a role in influencing a customer to buy the advertised product. The influence of an advertisement on a particular customer is considered the advertisement’s individual treatment effect (ITE). This study estimates ITE from data in which units are potentially c

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Jerome J. Decosse,Paul Sherlockof objective functions for neural models can be divided into metric learning and statistical learning. Metric learning approaches require a pair mining strategy that often lacks efficiency, while statistical learning approaches are not generating highly compact features due to their indirect feature

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Mysteries of the Uterine Cavitynon-linearity present in traffic data has posed a significant challenge to the modeling of accurate traffic forecasting systems. Lately, there has been a significant effort to develop complex Spatial-Temporal Graph Neural Networks (STGNN) that predominantly utilize various Graph Neural Networks (GNN