PEGE replaces the straight-through estimator with a curriculum-driven blend of quantized and full-precision weights plus an additive discretization-error correction, reporting small accuracy gains on low-bit CNNs.
Automatic at- tention pruning: Improving and automating model pruning using attentions
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Progressive Element-wise Gradient Estimation for Neural Network Quantization
PEGE replaces the straight-through estimator with a curriculum-driven blend of quantized and full-precision weights plus an additive discretization-error correction, reporting small accuracy gains on low-bit CNNs.