Hyperparameter Sensitivity in Deep Outlier Detection: Analysis and a Scalable Hyper-Ensemble Solution. (arXiv:2206.07647v1 [cs.LG])

Web: http://arxiv.org/abs/2206.07647

Outlier detection (OD) literature exhibits numerous algorithms as it applies
to diverse domains. However, given a new detection task, it is unclear how to
choose an algorithm to use, nor how to set its hyperparameter(s) (HPs) in
unsupervised settings. HP tuning is an ever-growing problem with the arrival of
many new detectors based on deep learning. While they have appealing properties
such as task- driven representation learning and end-to-end optimization, deep
models come with a long list of HPs. Surprisingly, …

analysis arxiv deep detection ensemble lg scalable