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Download fileRandom Fourier Feature Based Deep Learning for Wireless Communications
This paper provides analytical results on fixed kernel width based RFF based DL (RFF-DL). The derived analysis and the presented case-studies indicate the RFF-DL's robustness to kernel-width initializations, and offers improved convergence in the low-data regime.
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Email Address of Submitting Author
rangeet.mitra.1@ens.etsmtl.caSubmitting Author's Institution
ETS MontrealSubmitting Author's Country
- India