An efficient mixing-matrix design algorithm for SGP that uses graph-theoretic parameters to reduce convergence time in broadcast DFL while providing performance guarantees.
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2026 2verdicts
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SinFormer is a tailored transformer that applies multi-scale self-attention and staged training to improve accuracy and robustness in radio frequency fingerprint identification on real-world data.
citing papers explorer
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Optimizing Stochastic Gradient Push under Broadcast Communications
An efficient mixing-matrix design algorithm for SGP that uses graph-theoretic parameters to reduce convergence time in broadcast DFL while providing performance guarantees.
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SinFormer: A Tailored Transformer for Robust Radio Frequency Fingerprint Identification
SinFormer is a tailored transformer that applies multi-scale self-attention and staged training to improve accuracy and robustness in radio frequency fingerprint identification on real-world data.