What is recorded here?
Used scaled stochastic ternary gradients with shared scaling/parameter localization, plus layerwise quantization and clipping to reduce synchronization traffic in distributed training.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Unbiased rounding assumes the specified unmodified gradient/scaler distribution; clipping changes the target estimator. Original convergence needs a single attracting minimum, summable-squared but non-summable steps and a stronger mixed-norm gradient bound, not arbitrary nonconvex neural loss. Aggregated multiworker gradients are not necessarily ternary; measured accuracy and modeled communication ratios are task/hardware-specific.
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People and systems
Wei Wen; Cong Xu; Feng Yan; Chunpeng Wu; Yandan Wang; Yiran Chen; Hai Li
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
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English catalogue narrative
TernGrad: stochastic ternary gradients for distributed training
Used scaled stochastic ternary gradients with shared scaling/parameter localization, plus layerwise quantization and clipping to reduce synchronization traffic in distributed training.
Scientific scope
Unbiased rounding assumes the specified unmodified gradient/scaler distribution; clipping changes the target estimator. Original convergence needs a single attracting minimum, summable-squared but non-summable steps and a stronger mixed-norm gradient bound, not arbitrary nonconvex neural loss. Aggregated multiworker gradients are not necessarily ternary; measured accuracy and modeled communication ratios are task/hardware-specific.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Wei Wen; Cong Xu; Feng Yan; Chunpeng Wu; Yandan Wang; Yiran Chen; Hai Li
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.