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Error-feedback SGD: biased-compression counterexamples and residual correction

Contribution grade

Compressed stochastic optimization · Human-designed research method or resource

Reference score145,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Exhibited convex failure cases for naive sign compression and used stored compression residuals in future updates, analyzing error-feedback SGD and scaled sign variants.

Scientific scope

Exhibited convex failure cases for naive sign compression and used stored compression residuals in future updates, analyzing error-feedback SGD and scaled sign variants. Inherits earlier error-feedback implementations and convex analyses; contribution is broader corrective analysis/counterexamples, not invention of all feedback. Positive rates require a delta-approximate compressor, unbiased bounded-moment stochastic gradients and stated smoothness/convexity assumptions. Compression terms remain in higher-order smooth bounds and leading nonsmooth bounds; not arbitrary broken compressors or literally free computation/communication.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Inherits earlier error-feedback implementations and convex analyses; contribution is broader corrective analysis/counterexamples, not invention of all feedback. Positive rates require a delta-approximate compressor, unbiased bounded-moment stochastic gradients and stated smoothness/convexity assumptions. Compression terms remain in higher-order smooth bounds and leading nonsmooth bounds; not arbitrary broken compressors or literally free computation/communication.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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