Dr. James McCaffrey of Microsoft Research tackles the process of examining a set of source data to find data items that are different in some way from the majority of the source items. Data anomaly ...

Data anomaly detection is the process of examining a set of source data to find data items that are different in some way from the majority of the source items. There are many different types of ...

Anomaly detection in the context of data science is detecting a data sample that is out of the ordinary and does not fit into the general data pattern (or an outlier). This deviation can result from a ...

Kalyan Veeramachaneni and his team at the MIT Data-to-AI (DAI) Lab have developed the first generative model, the AutoEncoder with Regression (AER) for time series anomaly detection, that combines ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. This article dives into the happens-before ...

If you run a quick web search on "machine learning use cases," you will find pages and pages of links to documents describing machine learning (ML) algorithms to detect or predict some kind of event ...

Acceldata, a leading provider of data observability and agentic data management solutions, is announcing a new capability designed to amplify the power of agentic reasoning within the company’s xLake ...

One key part of Microsoft’s big bet on machine learning is that these technologies need to be democratized, turned into relatively simple-to-understand building blocks that Microsoft’s developer ...