The Dataspace in the Sky integrates Federated Learning (FL), a decentralized Machine Learning (ML) approach that enhances security and privacy by sharing models instead of raw data, facilitating effective drone collaboration. However, the quality of shared local models often suffers due to ...
The smart collection and sharing of data is an important part of cloud-based systems, since huge amounts of data are being created all the time. This feature allows users to distribute data to particular recipients, while also allowing data proprietors t
We say this\(\textsf {MCFE}\)is\(\texttt {IND} \)-secure if for any adversary\(\mathcal {A}\),\(\mathsf {Adv}^{\texttt {IND}}(\mathcal {A}) = |P[\beta = 1 | b = 1] - P[\beta = 1 | b = 0]|\)is negligible. Informally, this is the usual Left-or-Right indi...
Data availability MNIST data set is publicly available.References [1] Lian X., Zhang C., Zhang H., Hsieh C.-J., Zhang W., Liu J. Can decentralized algorithms outperform centralized algorithms? A case study for decentralized parallel stochastic gradient descent Adv. Neural Inf. Process. Syst...
2Citations Abstract We describe the value of decentralized decision-making in the context of the assessment of systemic risks in the financial ecosystem and draw parallels to the lessons learned from the polycentric provision of local public goods. Greater resilience of the ecosystem requires methods ...
This article presents an advanced parameter-free velocity observer-based nonlinear decentralized tension control scheme for roll-to-roll systems governed b
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By using Secret Sharing and Multi-Secret Sharing directly in FL, it is not guaranteed that the participants will not access or infer information about the data or the models of the other participants since they will have access to the individual models. However, by combining Multi-Secret ...
Adv. Neural Inf. Process. Syst. 2017, 30, 104. [Google Scholar] Yin, D.; Chen, Y.; Kannan, R.; Bartlett, P. Byzantine-robust distributed learning: Towards optimal statistical rates. In Proceedings of the International Conference on Machine Learning, PMLR, Stockholm, Sweden, 10–15 July ...
Adv. Neural Inf. Process. Syst. 2017, 30, 104. [Google Scholar] Yin, D.; Chen, Y.; Kannan, R.; Bartlett, P. Byzantine-robust distributed learning: Towards optimal statistical rates. In Proceedings of the International Conference on Machine Learning, PMLR, Stockholm, Sweden, 10–15 July ...