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, sensor failures, or the aggregation of datasets from multiple sources. There is a rich literature on how to impute missing values, for example, considering the EM algorithm [Dempster et al., 1977], low
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train robust machine learning (ML) algorithms without exchanging the actual data. The benefits of such a decentralized technology over personal and confidential data are multiple and already include some
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financially viable solutions. At the heart of this mission is our Business Development Office (BDO), which drives business development, technology transfer, intellectual property management, and strategic
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motivated the development of Federated Learning (FL) [1,2], a framework for on-device collaborative training of machine learning models. FL algorithms like FedAvg [3] allow clients to train a common global
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interdisciplinary, and together we contribute to science and society. Your role The Research and Development Specialist will be responsible for establishing, developing and maintaining new and existing computational
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biomedical and clinical data. We are internationally recognized for our GDPR compliant data hosting solutions and data management systems. We develop innovative methodologies for data mining, federated data
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to health and disease remains poorly understood. The Systems Ecology group has developed an in vitro gut-on-a-chip model to study the human-microbial crosstalk. HuMiX mimics closely the physiological
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slicing. - Develop advanced AI/ML algorithms and data analytics techniques to automate and optimise exposure requests, adapted to available resources and real-time demand. - Propose and
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analyzed. The tensor model structure estimated by suitable optimization algorithms, such as that recently developed in [GOU20], will be considered as a starting point. • Exploiting data multimodality and
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identify optimal or near-optimal solutions. To address these challenges, CEA has developed A-DECA (Architecture Design Exploration and Configuration Automation), an in-house Electronic Design Automation (EDA