Hybrid Weight Representation: A Quantization Method Represented with Ternary and Sparse-Large Weights

ICLR 2020 Anonymous

Previous ternarizations such as the trained ternary quantization (TTQ), which quantized weights to three values (e.g., {−Wn, 0,+Wp}), achieved the small model size and efficient inference process. However, the extreme limit on the number of quantization steps causes some degradation in accuracy... (read more)

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