https://github.com/jiecaoyu/reading_list

https://github.com/jiecaoyu/reading_list

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• Host: GitHub
• URL: https://github.com/jiecaoyu/reading_list
• Owner: jiecaoyu
• Created: 2017-06-12T17:10:01.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2017-09-02T05:55:45.000Z (about 7 years ago)
• Last Synced: 2024-04-23T04:54:01.419Z (5 months ago)
• Size: 8.79 KB
• Stars: 6
• Watchers: 4
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Intro

I am Jiecao YU, a PhD student in the University of Michigan.

This is a paper reading list about DNN acceleration (also general Deep Learning).

Still under construction.

# DNN Acceleration

## DNN architecture

- MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

[ [paper](https://arxiv.org/pdf/1704.04861.pdf) | 20170612001 ]

- LightRNN: Memory and Computation-Efficient Recurrent Neural Networks

[ [paper](https://arxiv.org/pdf/1610.09893.pdf) | 20170612005 ]

- ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices

[ [paper](https://128.84.21.199/abs/1707.01083) | 20170713001 ]

## Accelerators

- Minerva: Enabling Low-Power, Highly-Accurate Deep Neural Network Accelerators

[ [paper](http://vlsiarch.eecs.harvard.edu/wp-content/uploads/2016/05/reagen_isca16.pdf) | 20170630001 ]

## DNN pruning

- Pruning Convolutional Neural Networks for Resource Efficient Transfer Learning

[ [paper](https://arxiv.org/pdf/1611.06440.pdf) | 20170612002 ]

- Learning Structured Sparsity in Deep Neural Networks

[ [paper](https://arxiv.org/pdf/1608.03665.pdf) | 20170612003 ]

- Dynamic Network Surgery for Efficient DNNs

[ [paper](https://arxiv.org/pdf/1608.04493.pdf) | 20170612004 ]

- Pruning Filters for Efficient ConvNets

[ [paper](https://arxiv.org/pdf/1608.08710.pdf) | 20170901001 ]

- Data-Driven Sparse Structure Selection for Deep Neural Networks

[ [paper](https://arxiv.org/pdf/1707.01213.pdf) | 20170901002 ]

- ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression

[ [paper](http://lamda.nju.edu.cn/luojh/project/ThiNet_ICCV17/ThiNet_ICCV17.html) | 20170901003 ]

- Scalpel: Customizing DNN Pruning to the Underlying Hardware Parallelism

[ [paper](http://www-personal.umich.edu/~jiecaoyu/papers/jiecaoyu-isca17.pdf) | 20170901004 ]

## Binarized neural network

- Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

[ [paper](https://arxiv.org/pdf/1602.02830.pdf) | 20170901005 ]

- XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks

[ [paper](https://arxiv.org/pdf/1603.05279.pdf) | 20170901006 ]

# Others