A correlation-based taxonomy unifies existing FL compression methods, experiments show correlation strengths vary by task and architecture, and adaptive mode-switching designs are proposed to exploit this.
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Exploiting Correlations in Federated Learning: Opportunities and Practical Limitations
A correlation-based taxonomy unifies existing FL compression methods, experiments show correlation strengths vary by task and architecture, and adaptive mode-switching designs are proposed to exploit this.