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Towards Real-Time DNN Inference on Mobile Platforms with Model Pruning and Compiler Optimization.

, , , , , и . IJCAI, стр. 5306-5308. ijcai.org, (2020)Demo.

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Zhan Kang

Zhan Gao

Zheng-Zheng Kuang

Renya Zhan

Beibei Zhan

 

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A new theory of complexity science management - Big organization., , , , и . GrC, стр. 449-458. IEEE Computer Society, (2013)All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management., , , , , , , , и . ICCAD, стр. 133:1-133:9. ACM, (2022)MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge., , , , , , , , , и 6 other автор(ы). NeurIPS, стр. 20838-20850. (2021)A Privacy-Preserving-Oriented DNN Pruning and Mobile Acceleration Framework., , , , , , , , , и 1 other автор(ы). ACM Great Lakes Symposium on VLSI, стр. 119-124. ACM, (2020)A novel damage identification algorithm by combining the boundary element method and a series connection neural network., , и . Eng. Appl. Artif. Intell., (2024)Representation Learning on Spatial Networks., и . NeurIPS, стр. 2303-2318. (2021)Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-Resolution., , , , , , , , , и . ECCV (19), том 13679 из Lecture Notes in Computer Science, стр. 92-111. Springer, (2022)A Unified DNN Weight Pruning Framework Using Reweighted Optimization Methods., , , , , , и . DAC, стр. 493-498. IEEE, (2021)A new algorithm for water information extraction from high resolution remote sensing imagery., , , , и . ICIP, стр. 4359-4363. IEEE, (2016)Towards Real-Time DNN Inference on Mobile Platforms with Model Pruning and Compiler Optimization., , , , , и . IJCAI, стр. 5306-5308. ijcai.org, (2020)Demo.