Heterogeneous Bitwidth Binarization in Convolutional Neural Networks

Imagenet classification with deep convolutional neural networks

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Compressing deep convolutional networks using vector quantization

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Courbariaux, Matthieu, Bengio, Yoshua, and David, Jean-Pierre · 2015

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Going deeper with convolutions

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Binarized neural networks: Training deep neural networks with weights and activations constrained to+ 1 or-1

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Courbariaux, Matthieu, Hubara, Itay, Soudry, Daniel, El-Yaniv, Ran, and Bengio, Yoshua · 2016

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Quantized neural networks: Training neural networks with low precision weights and activations

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Hubara, Itay, Courbariaux, Matthieu, Soudry, Daniel, El-Yaniv, Ran, and Bengio, Yoshua · 2016

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Ternary weight networks

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Li, Fengfu, Zhang, Bo, and Liu, Bin · 2016

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Xnor-net: Imagenet classification using binary convolutional neural networks

Rastegari, Mohammad, Ordonez, Vicente, Redmon, Joseph, and Farhadi, Ali · 2016

Ternary neural networks for resource-efficient ai applications

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Learning accurate low-bit deep neural networks with stochastic quantization

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Mobilenets: Efficient convolutional neural networks for mobile vision applications

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How to train a compact binary neural network with high accuracy?

Tang, Wei, Hua, Gang, and Wang, Liang · 2017

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Finn: A framework for fast, scalable binarized neural network inference

Umuroglu, Yaman, Fraser, Nicholas J, Gambardella, Giulio, Blott, Michaela, Leong, Philip, Jahre, Magnus, and Vissers, Kees · 2017