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1

Federated Learning: The Future of AI Without Compromising Privacy

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Federated Learning (FL) has become a paradigm-shifting technology in AI, allowing data scientists to work with private data. In comparison to the standard machine learning approach, where all the individual client data must be collected and moved to a centralized server, with the Federated Learning approach, model training can be done directly on the clients […]

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Fairness and Bias in AI Applications for the Labor Market

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For the 2024 Applied Machine Learning Days (AMLD) conference held at EPFL, the BFH Applied Machine Intelligence group and NLP expert Dr. Elena Nazarenko organized a track on fairness in AI applications in the labor market. The conference brings together over 1500 participants from over 40 countries across industry, academia, and government. For this year’s […]

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How forward-looking data governance enables the reuse of data

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“Open government data” is just the beginning. The end-to-end digitalisation of the public sector requires solid data governance with clear roles thataredesigned for the reuse of data Various federal, cantonal and municipal authorities are already publishing open government data (OGD). The media, companies and other interested parties can use the data freely, for example to […]