SPARK: Efficient Decentralized Learning Through Stage-wise Projected NTK and Accelerated Regularization
Published:Dec 14, 2025 15:21
•1 min read
•ArXiv
Analysis
The paper presents SPARK, a novel approach for communication-efficient decentralized learning. It leverages stage-wise projected Neural Tangent Kernel (NTK) and accelerated regularization techniques to improve performance in decentralized settings, a significant contribution to distributed AI research.
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Reference
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