This is the first comprehensive survey of OOD generalization methodologies for time series, organized across data distribution, representation learning, and OOD evaluation.
In: Proceedings of the 29th ACM SIGKDD Conf
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XGBoost-Forget applies machine unlearning to XGBoost on IoT-23 and GeNIS network intrusion datasets, achieving faster forgetting with maintained predictive performance.
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Out-of-Distribution Generalization in Time Series: A Survey
This is the first comprehensive survey of OOD generalization methodologies for time series, organized across data distribution, representation learning, and OOD evaluation.
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Machine Unlearning for the XGBoost Model with Network Intrusion Datasets
XGBoost-Forget applies machine unlearning to XGBoost on IoT-23 and GeNIS network intrusion datasets, achieving faster forgetting with maintained predictive performance.