In the last decade, auxiliary information has been widely used to address data sparsity. Due to the advantages of feature extraction and the no-label requirement, autoencoder-based methods addressing ...

Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a dataset that are different from the majority for tasks like ...

Anomaly detection is the process of finding items in a dataset that are different in some way from the majority of the items. For example, you could examine a dataset of credit card transactions to ...