Shard the Gradient, Scale the Model: Serverless Federated Aggregation via Gradient Partitioning
arXiv 2604.22072•e78093c0be3f7dd22df0ccc8cdf84df427d936eed50327646a1351ed58d8072f
arxivcloud-computingdistributed-systemsepidemic-modelingfederated-learninggpuhigh-performance-computingllm-servingmachine-learningnetworkingresearchresource-managementserverless
Paper metadata
- arXiv ID
- 2604.22072
- Version
- Not specified by this published record
- Category
- Computer Science — Distributed, Parallel, and Cluster Computing (cs.DC)
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Evidence and limitations
- Source ID
- arxiv_cs_dc
- Record identifier
- e78093c0be3f7dd22df0ccc8cdf84df427d936eed50327646a1351ed58d8072f
- Enrichment time
- 2026-08-16T13:05:47Z
- AI-assisted enrichment
- Yes
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