Fundamental Limits of Communication Efficiency for Model Aggregation in Distributed Learning: A Rate-Distortion Approach

Research article (IEEE Transactions on Communications, 2022) · cited 15× · AI/ML
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Fundamental Limits of Communication Efficiency for Model Aggregation in Distributed Learning: A Rate-Distortion Approach

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Fundamental Limits of Communication Efficiency for Model Aggregation in Distributed Learning: A Rate-Distortion Approach is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Fundamental Limits of Communication Efficiency for Model Aggregation in Distributed Learning: A Rate-Distortion Approach. Retrieved May 24, 2026, from https://4ort.xyz/entity/fundamental-limits-of-communication-efficiency-for-model-aggregation-in-distributed-learning-a-rate-distortion-approach
MLA “Fundamental Limits of Communication Efficiency for Model Aggregation in Distributed Learning: A Rate-Distortion Approach.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/fundamental-limits-of-communication-efficiency-for-model-aggregation-in-distributed-learning-a-rate-distortion-approach.
BibTeX @misc{4ortxyz_fundamental-limits-of-communication-efficiency-for-model-aggregation-in-distributed-learning-a-rate-distortion-approach_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Fundamental Limits of Communication Efficiency for Model Aggregation in Distributed Learning: A Rate-Distortion Approach}}, year = {2026}, url = {https://4ort.xyz/entity/fundamental-limits-of-communication-efficiency-for-model-aggregation-in-distributed-learning-a-rate-distortion-approach}, note = {Accessed: 2026-05-24}}
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