UFLDL Recommended Readings

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If you're learning about UFLDL (Unsupervised Feature Learning and Deep Learning), here is a list of papers to consider reading.  
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If you're learning about UFLDL (Unsupervised Feature Learning and Deep Learning), here is a list of papers to consider reading.  We're assuming you're already familiar with basic machine learning at the level of [[http://cs229.stanford.edu/ CS229 (lecture notes available)]].  
The basics:  
The basics:  
* [[http://cs294a.stanford.edu CS294A]] neural network/sparse autoencoder tutorial. (Most of this is now in the [[UFLDL Tutorial]], but the exercise is still on the CS294A website.)  
* [[http://cs294a.stanford.edu CS294A]] neural network/sparse autoencoder tutorial. (Most of this is now in the [[UFLDL Tutorial]], but the exercise is still on the CS294A website.)  
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* Natural Image Statistics book, Hyvarinen et al.  
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* Natural Image Statistics book, Hyvarinen et al. This is long, so just skim or skip the chapters that you already know.  Important chapters: 5 (PCA and whitening; you'll probably already know the PCA stuff), 6 (sparse coding), 7 (ICA), 10 (ISA), 11 (TICA), 16 (temporal models). 
* Olshausen and Field Sparse Coding paper (1996)  
* Olshausen and Field Sparse Coding paper (1996)  
* [http://www.cs.stanford.edu/~ang/papers/icml07-selftaughtlearning.pdf]  Rajat Raina, Alexis Battle, Honglak Lee, Benjamin Packer and Andrew Y. Ng. Self-taught learning: Transfer learning from unlabeled data. ICML 2007
* [http://www.cs.stanford.edu/~ang/papers/icml07-selftaughtlearning.pdf]  Rajat Raina, Alexis Battle, Honglak Lee, Benjamin Packer and Andrew Y. Ng. Self-taught learning: Transfer learning from unlabeled data. ICML 2007
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Applications:
Applications:
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* Object Recognition
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* Computer Vision
** [http://www.ifp.illinois.edu/~jyang29/ScSPM.htm] Jianchao Yang, Kai Yu, Yihong Gong, Thomas Huang. Linear Spatial Pyramid Matching using Sparse Coding for Image Classification, CVPR 2009  
** [http://www.ifp.illinois.edu/~jyang29/ScSPM.htm] Jianchao Yang, Kai Yu, Yihong Gong, Thomas Huang. Linear Spatial Pyramid Matching using Sparse Coding for Image Classification, CVPR 2009  
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** Small codes and large image databases for recognition.  Torralba, Fergus, Weiss.
* Audio Recognition
* Audio Recognition
** [http://www.cs.stanford.edu/people/ang/papers/nips09-AudioConvolutionalDBN.pdf] Unsupervised feature learning for audio classification using convolutional deep belief networks, Honglak Lee, Yan Largman, Peter Pham and Andrew Y. Ng. In NIPS*2009.
** [http://www.cs.stanford.edu/people/ang/papers/nips09-AudioConvolutionalDBN.pdf] Unsupervised feature learning for audio classification using convolutional deep belief networks, Honglak Lee, Yan Largman, Peter Pham and Andrew Y. Ng. In NIPS*2009.
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Revision as of 02:13, 1 March 2011

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