Anomaly detection using feedback training

US11983243B2 · kind B2 · utility

Assignee

• AMAZON TECHNOLOGIES, INC. · US

Inventors

• Barath Balasubramanian · Cambridge, US
• Rahul Bhotika · Albany, US
• Niels Brouwers · New York, US
• Ranju Das · Seattle, US
• Prakash Krishnan · Santa Clara, US
• Shaun Ryan James McDowell · Great Neck, US
• Anushri Mainthia · Seattle, US
• Rakesh Madhavan Nambiar · Seattle, US
• Anant Patel · Seattle, US
• Avinash Aghoram Ravichandran · Baltimore, US
• Joaquin Zepeda Salvatierra · Mercer Island, US
• Gurumurthy Swaminathan · Redmond, US

Key dates

• Filing date: Nov 27, 2020
• Grant date: May 14, 2024
• Expiry date: Apr 5, 2042

Classification

• Technology area (CPC G): Physics
• CPC primary: G06T2207/20081
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

Techniques for anomaly detection are described. An exemplary method includes receiving one or more requests to train an anomaly detection machine learning model using feedback-based training, the request to indicate one or more of a type of analysis to perform, a model selection indication, and a configuration for a training dataset; training the anomaly detection machine learning model according to the one or more requests using the training data; performing feedback-based training on the trained anomaly detection machine learning model; and using the retrained anomaly detection machine learning model.