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- W3201216690 abstract "The performance of over-the-air computation-based fast model aggregation approach presented in the previous chapters heavily depends on instantaneous channel state information (CSI). Acquiring CSI for federated learning systems with massive mobile devices leads to large amount of signaling overhead. To address this issue, in this chapter, we provide a blind over-the-air computation approach for low-overhead fast model aggregation by exploiting the blind demixing technique for transceivers design without CSI information. We formulate a bilinear unconstrained optimization problem and present a Wirtinger flow solution, which enjoys global convergence guarantee. Simulation results demonstrate that the aggregation results can be efficiently computed over-the-air without knowing instantaneous CSI." @default.
- W3201216690 created "2021-09-27" @default.
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- W3201216690 date "2022-01-01" @default.
- W3201216690 modified "2023-10-18" @default.
- W3201216690 title "Blind over-the-air computation for federated learning" @default.
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- W3201216690 doi "https://doi.org/10.1016/b978-0-12-823817-2.00021-8" @default.
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