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README.md

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 # Fast and Scalable Machine Learning: Algorithms and  Systems
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 A collection of papers about recent progress on machine learning and systems, covering following topics:
 

dl_cnn.md

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 ## Convolutional Nerual Netowrks
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 ##### ImageNet Records  
 - 2016 arXiv [Identity Mappings in Deep Residual Networks](http://arxiv.org/pdf/1603.05027v1.pdf)    

dl_opt.md

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 ## Optimization 
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 - 2016 ICLR [Data-Dependent Path Normalization in Neural Networks](http://arxiv.org/pdf/1511.06747v4.pdf)  
 - 2016 Blog [An overview of gradient descent optimization algorithms](http://sebastianruder.com/optimizing-gradient-descent/index.html)  

dl_sys.md

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 ##Deep Learning Systems
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 ## Deep Learning Software / Frameworks
 - **[Caffe](http://caffe.berkeleyvision.org/)**  
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 	2016 arXiv [Theano: A Python framework for fast computation of mathematical expressions](http://arxiv.org/abs/1605.02688)  
 - **[Torch](http://torch.ch/)**  
 	2011 NIPSW [Torch7: A Matlab-like Environment for Machine Learning](http://cs.nyu.edu/~koray/files/2011_torch7_nipsw.pdf)  
-<!--- **Petuum**  
-	2016 EuroSys [STRADS: A Distributed Framework for Scheduled Model Parallel Machine Learning](http://www.istc-cc.cmu.edu/publications/papers/2016/strads-kim-eurosys16.pdf)   -->
 
 ## Speicific System 
  - 2015 arXiv [Deep Speech 2: End-to-End Speech Recognition in English and Mandarin](http://arxiv.org/abs/1512.02595)  

matrix_fact.md

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 # Matrix Factorization
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 - 2016 WSDM [DiFacto — Distributed Factorization Machines](http://www.cs.cmu.edu/~yuxiangw/docs/fm.pdf)   
 - 2015 CIKM [HDRF: Stream-Based Partitioning for Power-Law Graphs](http://www.fabiopetroni.com/Download/petroni- 2015HDRF.pdf)