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 ...

Anomaly detection is one of the more difficult and underserved operational areas in the asset-servicing sector of financial institutions. Broadly speaking, a true anomaly is one that deviates from the ...

Anomaly detection in images is rapidly emerging as a critical field in both industrial quality control and medical diagnostics. Leveraging deep learning techniques, researchers have developed methods ...

Researchers used large language models to efficiently detect anomalies in time-series data, without the need for costly and cumbersome training steps. This method could someday help alert technicians ...

Security remains a dominant challenge in remote health monitoring. Medical data is deeply sensitive, and breaches can expose patients to identity theft, insurance exploitation or targeted cyberattacks ...

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 ...

Know why ML-driven anomaly detection is crucial for preventing malicious signature requests. Learn how machine learning identifies zero-day threats and secures crypto wallets.

The US Army Analytics Group (AAG) provides analytical services for various organizational operations and functions, including cybersecurity. AAG signed a Cooperative Research and Development Agreement ...