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Qinghua Yan

2 accepted papers

2022

BiBERT: Accurate Fully Binarized BERT

ICLR 2022poster

The large pre-trained BERT has achieved remarkable performance on Natural Language Processing (NLP) tasks but is also computation and memory expensive. As one of the powerful compression approaches, binarization extremely reduces the computation and memory consumption by utilizing 1-bit parameters a…

2021

Diversifying Sample Generation for Accurate Data-Free Quantization

CVPR 2021poster

Quantization has emerged as one of the most prevalent approaches to compress and accelerate neural networks. Recently, data-free quantization has been widely studied as a practical and promising solution. It synthesizes data for calibrating the quantized model according to the batch normalization (B…

Cited by 113PDFScholar