ML system proves adept at pinpointing power grid problems theregister.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from theregister.com Daily Mail and Mail on Sunday newspapers.
Researchers at the MIT-IBM Watson AI lab have developed a computationally efficient method that could be used to identify anomalies in the U.S. power grid in real time. The novel technique augments a special type of machine-learning model with a powerful graph structure, and does not require any labeled data to train.
Identifying a malfunction in the nation’s power grid can be like trying to find a needle in an enormous haystack. Hundreds of thousands of interrelated
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UNIVERSITY PARK, Pa. Did you ever wonder how social networking applications like Facebook and LinkedIn make recommendations on the people you should friend or pages you should follow?
Behind the scenes are machine learning models that classify nodes based on the data they contain about users for example, their level of education, location or political affiliation. The models then use these classifications to recommend people and pages to each user. But there is significant bias in the recommendations made by these models known as graph neural networks (GNNs) as they rely on user features that are highly related to sensitive attributes such as gender or skin color.