Finally, we held interactive sessions to complement the theoretical definition of the reference standards, and further guide collaborating sites. Particular pain points regarding these administrative tasks included managing the large volume of communication (i.e., emails and conference calls) needed to ...
[8] Dan Bogdanov, Sven Laur, and Jan Willemson. 2008. Sharemind: A Framework for Fast Privacy-Preserving Computations. In Proceedings of the 13th European Symposium on Research in Computer Security: Computer Security (ESORICS ’08). Springer-Verlag, Berlin, Heidelberg, 192–206. https://doi.o...
In subject area: Computer Science Federated learning is a type of distributed machine learning where machine learning and deep learning algorithms are trained on data from edge devices like laptops, smartphones, and wearable devices, without the need to transfer the data to a central server. This...
Now that we have established a solid understanding of identity, it’s time to discussfederated identity. We will cover the definition of federated identity and why you would want to use it. Federated identity is actually a combination of different components and concepts that come together to for...
Problem definition Based on aforementioned definitions, we can formulate an objective function for the FIL in Equation 1. $$\begin{aligned} \min _{\omega _{1, \dots ,P}}\sum _{i = 1}^P[F(\omega _i) + D(F(\omega _i), \mu )] \end{aligned}$$ (1) F is the loss functio...
The definition and classification of FL are described above. This section is mainly on its 5 unsolved problems. 3.1. The Problem of Nonindependent and Identically Distributed Data Samples In distributed ML, local data samples are often independently and identically distributed. Although FL is a kind...
(2021), which is often referred to as the first law on AI and is conceived for introducing a common regulatory and legal framework for AI. The European Commission had previously promoted the definition of the “Ethics guidelines for trustworthy AI” [1], which identifies lawfulness, ethics, ...
5.1 Criteria and weighting definition To ensure a detailed comparison, the FL frameworks are examined from three different perspectives, namely Features, Interoperability and User Friendliness using a weighted scoring system. All three main comparison categories each make up 100%. For each comparison cat...
By definition, FL enables multiple parties to jointly train an ML model without exchanging local data. It involves distributed systems, ML and privacy research areas (Kairouz et al., 2021, Li et al., 2019), and, since the pioneer FedAVG (Brendan McMahan et al., 2017) approach, many new...
Symbol Definition Ensemble WW W=Cl(2)⊗ nW=Cl(2)⊗ n Hermitian matrix OiOi OiOi is a kk-local Pauli observable Classical snapshot ^ρj(\bm θ)ρ^j(\bm θ) ^ρj(\bm θ)=⊗ns=1(3W†j,s |bj,s(\bmθ)⟩ ⟨ bj,s(\bmθ)| Wj,s−I)ρ^j(\bm θ)=⊗s=1n(3...