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HODEC: Towards Efficient High-Order DEcomposed ...
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由 M Yin 著作2022被引用 20 次 — High-order decomposition is a widely used model com- pression approach towards compact convolutional neural networks (CNNs). However, many of the existing ...
HODEC: Towards Efficient High-Order DEcomposed ...
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由 M Yin 著作2022被引用 20 次 — Abstract: High-order decomposition is a widely used model compression approach towards compact convolutional neural networks (CNNs).
Towards Efficient High-Order DEcomposed Convolutional ...
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Truncated singular value decomposition (TSVD) has good performance in decomposing matrices, however, compared to other tensor decomposition methods such as ...
HODEC: Towards Efficient High-Order DEcomposed ...
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由 M Yin 著作2022被引用 20 次 — High-order decomposition is a widely used model com- pression approach towards compact convolutional neural networks (CNNs). However, many of the existing ...
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Towards Efficient High-Order DEcomposed Convolutional ...
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Dive into the research topics of 'HODEC: Towards Efficient High-Order DEcomposed Convolutional Neural Networks'. Together they form a unique fingerprint. Sort ...
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ELRT: Towards Efficient Low-Rank Training for Compact Neural Networks · pdf ... HODEC: Towards Efficient High-Order DEcomposed Convolutional Neural Networks ...
Miao Yin
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High-order decomposition is a widely used model compression approach towards compact convolutional neural networks (CNNs). Model Compression · Vocal Bursts ...
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2022年6月1日 — HODEC: Towards Efficient High-Order DEcomposed Convolutional Neural Networks · Miao Yin · Sui Yang · Wanzhao Yang · Xiao Zang · Yu Gong · Bo Yuan ...
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... HODEC: Towards Efficient High-Order DEcomposed Convolutional Neural Networks." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022. [PDF]
Yang Sui
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High-order decomposition is a widely used model compression approach towards compact convolutional neural networks (CNNs). Model Compression · Vocal Bursts ...
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