Ps and Qs: Quantization-Aware Pruning for Efficient Low Latency Neural Network Inference

Benjamin Hawks, Javier Duarte, Nicholas J. Fraser, Alessandro Pappalardo, Nhan Tran, Yaman Umuroglu

Open source

DOI: 10.3389/frai.2021.676564
Published: 2021-07-09
Container: Frontiers in Artificial Intelligence
Publisher: Frontiers Media SA
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.3389/frai.2021.676564,
  title = {Ps and Qs: Quantization-Aware Pruning for Efficient Low Latency Neural Network Inference},
  author = {Benjamin Hawks and Javier Duarte and Nicholas J. Fraser and Alessandro Pappalardo and Nhan Tran and Yaman Umuroglu},
  year = {2021},
  journal = {Frontiers in Artificial Intelligence},
  doi = {10.3389/frai.2021.676564},
  url = {https://doi.org/10.3389/frai.2021.676564}
}

RIS

TY  - JOUR
TI  - Ps and Qs: Quantization-Aware Pruning for Efficient Low Latency Neural Network Inference
AU  - Benjamin Hawks
AU  - Javier Duarte
AU  - Nicholas J. Fraser
AU  - Alessandro Pappalardo
AU  - Nhan Tran
AU  - Yaman Umuroglu
PY  - 2021
JO  - Frontiers in Artificial Intelligence
DO  - 10.3389/frai.2021.676564
UR  - https://doi.org/10.3389/frai.2021.676564
ER  -

APA

Hawks, B., Duarte, J., Fraser, N. J., Pappalardo, A., Tran, N., & Umuroglu, Y. (2021). Ps and Qs: Quantization-Aware Pruning for Efficient Low Latency Neural Network Inference. Frontiers in Artificial Intelligence. https://doi.org/10.3389/frai.2021.676564

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crossref · retrieved 2026-09-25T09:14:57.605Z