Federated learning was devised to solve the problem of difficulty in aggregating personal data, such as patient medical records or financial data, in one place. However, during the process where each ...

Federated Learning was devised to solve the problem of difficulty in aggregating personal data, such as patient medical ...

The research also opens doors for broader applications of multi-objective optimization in renewable process engineering, from ...

GXIG’s deep learning model is trained through a four-step process designed to establish an optimal architecture for analysis ...

Abstract: Improving the generalization capability of vibration damper detection model for transmission lines is essential for its application in complex power scenarios. Variations in vibration damper ...

The latest Research.com rankings have named four Queen Mary researchers among the top 100 scientists in the UK, recognising ...

The study’s results show that enhanced generalization with suppression, the strongest de-identification strategy, ...

Srinivas Sujayendra's research and 17+ years of experience drive data modernization in healthcare and finance through ...

Algorithms developed by Professor Brokoslaw Laschowski (MIE) and his lab are being used to decode the brain and interface ...

With increase in the applications of autonomous systems, in both civilian and military domains, it has become increasingly important to provide formal ...

Traditional EDA tools rely on heuristics and static algorithms, which struggle to scale with modern design complexity. AI ...

Generation Z, the cohort born between the mid-1990s and the early 2010s, is often considered through the lens of broad generalizations. Labeled as hypersensitive ‘snowflakes’ and criticized as lacking ...