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Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions
22 November 2017
Bichen Wu
Alvin Wan
Xiangyu Yue
Peter H. Jin
Sicheng Zhao
Noah Golmant
A. Gholaminejad
Joseph E. Gonzalez
Kurt Keutzer
3DPC
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Papers citing
"Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions"
50 / 164 papers shown
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Visual Transformers: Token-based Image Representation and Processing for Computer Vision
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03 Jun 2020
AlignShift: Bridging the Gap of Imaging Thickness in 3D Anisotropic Volumes
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Yi He
Xiaoyang Huang
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Zining Wang
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Masayoshi Tomizuka
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231
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Weizhe Hua
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158
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145
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233
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Hanting Chen
Yunhe Wang
Chunjing Xu
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Efficient Error-Tolerant Quantized Neural Network Accelerators
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Domain-Aware Dynamic Networks
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151
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Efficient Hardware Implementation of Incremental Learning and Inference on Chip
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G. B. Hacene
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M. Arzel
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Accelerating Training using Tensor Decomposition
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136
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Full-Stack Filters to Build Minimum Viable CNNs
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Attention Based Pruning for Shift Networks
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Incremental Learning Using a Grow-and-Prune Paradigm with Efficient Neural Networks
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DARC: Differentiable ARchitecture Compression
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