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An All-Reduce Compatible Top-K Compressor for Communication-Efficient Distributed Learning

arXiv — cs.LG•Monday, November 3, 2025 at 5:00:00 AM
PositiveArtificial Intelligence
A new study introduces an innovative Top-K compressor designed to enhance communication efficiency in distributed machine learning. This advancement addresses the significant bottleneck of communication in large-scale systems by improving upon existing gradient compression methods. Unlike previous approaches that either discard vital information or require expensive operations, this new method aims to retain essential data while minimizing costs. This development is crucial as it could lead to faster and more effective machine learning processes, making it a significant step forward in the field.
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