Depeng Xu

Fine-grained Anomaly Detection in Sequential Data via Counterfactual Explanations

2022 · arXiv (Cornell University)

Anomaly detection in sequential data has been studied for a long time because of its potential in various applications, such as detecting abnormal system behaviors from log data. Although many approaches can achieve good performance …

Few-shot Anomaly Detection and Classification Through Reinforced Data Selection

2022 · 2022 IEEE International Conference on Data Mining (ICDM)

Due to the scarcity of anomalies, deep anomaly detection models are predominately trained in an unsupervised or semi-supervised manner depending on the availability of a small number of labeled samples. Currently, most unsupervised approaches detect …