NetSenseML adaptively sets gradient compression ratios from real-time bandwidth and round-trip time measurements, improving training throughput in constrained networks while aiming to preserve model accuracy.
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NetSenseML: Network-Adaptive Compression for Efficient Distributed Machine Learning
NetSenseML adaptively sets gradient compression ratios from real-time bandwidth and round-trip time measurements, improving training throughput in constrained networks while aiming to preserve model accuracy.