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Sökning: WFRF:(Ács Gergely)

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1.
  • Buttyan, Levente, et al. (författare)
  • Dependability concepts, models, and analysis of networking mechanisms for WSANs
  • 2009
  • Rapport (övrigt vetenskapligt/konstnärligt)abstract
    • In this deliverable, we report on the results of Work Package 3 (Dependable Networking) obtained in the first year of the WSAN4CIP Project. These results are related to the identification of the design principles of dependable networking mechanisms for WSANs. In our work, and hence, in this deliverable, we follow the layered model of networking protocol stacks: We identify the most important dependability concepts and models at the physical, MAC (Medium Access Control), routing, and transport layers, and we analyze existing networking protocols from the different layers proposed in the literature with respect to the identified dependability properties.
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2.
  • Oldenhof, Martijn, et al. (författare)
  • Industry-Scale Orchestrated Federated Learning for Drug Discovery
  • 2023
  • Ingår i: Proceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023. ; 37, s. 15576-15584
  • Konferensbidrag (refereegranskat)abstract
    • To apply federated learning to drug discovery we developed a novel platform in the context of European Innovative Medicines Initiative (IMI) project MELLODDY (grant n°831472), which was comprised of 10 pharmaceutical companies, academic research labs, large industrial companies and startups. The MELLODDY platform was the first industry-scale platform to enable the creation of a global federated model for drug discovery without sharing the confidential data sets of the individual partners. The federated model was trained on the platform by aggregating the gradients of all contributing partners in a cryptographic, secure way following each training iteration. The platform was deployed on an Amazon Web Services (AWS) multi-account architecture running Kubernetes clusters in private subnets. Organisationally, the roles of the different partners were codified as different rights and permissions on the platform and administrated in a decentralized way. The MELLODDY platform generated new scientific discoveries which are described in a companion paper.
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