ニュース

Visual Studio Magazine1年

Data Anomaly Detection Using a Neural Autoencoder with C#

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 ...
Visual Studio Magazine1年

Data Anomaly Detection Using a Neural Autoencoder with C#

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 ...
Scientific Research Publishing4 日

Agentic AI in Contract Analytics Harnessing Machine Learning for Risk Assessment and ...

Government procurement contracts can be complicated, with extensive risk analysis and compliance reviews. The traditional ...
MSN による配信10月

CMS develops new AI algorithm to detect anomalies at the Large Hadron Collider

In the quest to uncover the fundamental particles and forces of nature, one of the critical challenges facing high-energy experiments at the Large Hadron Collider (LHC) is ensuring the quality of the ...
TechCrunch4年

Financial firms should leverage machine learning to make anomaly detection easier

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 ...
Scientific Research Publishing9 日

Risk-Aware AI Models for Financial Fraud Detection: Scalable Inference from Big ...

Sethupathy, U. (2025) Risk-Aware AI Models for Financial Fraud Detection: Scalable Inference from Big Transactional Data.
Harvard Business School3年

Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and ...

Cintas, Celia, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan, and Edward McFowland III. "Detecting Adversarial Attacks ...