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cs.LG2025
Positive-Unlabeled Diffusion Models for Preventing Sensitive Data Generation
Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai +2
Diffusion models are powerful generative models but often generate sensitive data that are unwanted by users, mainly because the unlabeled training data frequently contain such sen…
cs.LG2024
LogELECTRA: Self-supervised Anomaly Detection for Unstructured Logs
Yuuki Yamanaka, Tomokatsu Takahashi, Takuya Minami +1
System logs are some of the most important information for the maintenance of software systems, which have become larger and more complex in recent years. The goal of log-based ano…