“Readings”版本间的差异

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=Speech recognition=
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[[New member reading list]]
  
1. Noise robustness
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[[Advanced member reading list]]
  
http://www1.icsi.berkeley.edu/Speech/papers/gelbart-ms/pointers/
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[[Public Research Tools]]
  
2. Qualcomm-ICSI-OGI front end
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[[People you may want to follow]]
http://www1.icsi.berkeley.edu/Speech/papers/qio/
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=Machine Learning=
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[[Other teams]]
  
1. general Bayesian inference: doc and tool
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[[Journals you may submit to]]
  
http://ksvanhorn.com/bayes/free-bayes-software.html
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[[Free libraries]]
  
2. The Variantional Bayesian toolkit:
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[[Data resources]]
  
http://www.gatsby.ucl.ac.uk/vbayes/vbsoftware.html
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[[Seminars]]
  
The sampling based Bayesian approach can be obtained here:
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[[Machine Learning Book]]
  
http://www.mrc-bsu.cam.ac.uk/bugs/
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[[AI Book]]
 
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3. Topic models from David Blei
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http://www.cs.princeton.edu/~blei/topicmodeling.html
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4. MCMC approaches also here
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http://www.mppmu.mpg.de/bat/
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http://www.mpe.mpg.de/~aws/BayesForum_201204_KK.pdf
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5. Topic models Biography
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http://www.cs.princeton.edu/~mimno/topics.html
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6. Gibbs LDA
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http://gibbslda.sourceforge.net/
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7. Tools for DPMM
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Jacobei
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https://github.com/jacobeisenstein/DPMM
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Sickit
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http://scikit-learn.org/0.11/index.html
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Hains
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http://code.google.com/p/haines/
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8. Sparse SVMs
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http://www.enm.bris.ac.uk/staff/xkh/
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9. Lasso
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http://www-stat.stanford.edu/~tibs/lasso.html
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10. Sparse LU
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http://crd-legacy.lbl.gov/~xiaoye/SuperLU/
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11. Ensemble SVM
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http://homes.esat.kuleuven.be/~claesenm/ensemblesvm/
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12. Online learning toolkit
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http://www.cais.ntu.edu.sg/~chhoi/libol/
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13. VBEM-GMM
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http://www.cs.ubc.ca/~murphyk/Software/VBEMGMM/index.html
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=NLP toolkits and resources=
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1. Stanford tools
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http://nlp.stanford.edu/software/
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2. Traditional Chinese public dictionary and statistics
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http://www.edu.tw/files/site_content/m0001/pin/yu7.htm?open
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3. Idiom Traditional Chinese public words
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http://dict.idioms.moe.edu.tw/cydic/index.htm
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4. RNN toolkit from microsoft
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http://research.microsoft.com/en-us/projects/rnn/
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5. A bunch of resources
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http://www-nlp.stanford.edu/links/statnlp.html
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=SID toolits=
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1. Alize from Avignon
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http://mistral.univ-avignon.fr/download_en.html
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2. Idiap
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https://github.com/bioidiap/xbob.spkrec
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http://www.idiap.ch/~marcel/professional/Resources.html
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=People you may want to follow=
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1. Dong Yu, MS
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http://research.microsoft.com/en-us/people/dongyu/
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2. Geoffrey E. Hinton, U. Toronto
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http://www.cs.toronto.edu/~hinton/
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3. Deng Li, MS
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http://research.microsoft.com/en-us/people/deng/
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4. Tara Sainath, IBM
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http://www.researchgate.net/profile/Tara_Sainath/publications/
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http://www.informatik.uni-trier.de/~ley/pers/hd/s/Sainath:Tara_N=.html
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5. Daniel Povey, JHU
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http://www.danielpovey.com/
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6. Patrick Kenny, CRIM
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http://www.crim.ca/perso/patrick.kenny/
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7. Nelson Morgan, ICSI Berkley
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http://www1.icsi.berkeley.edu/~morgan/
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2018年8月23日 (四) 13:50的最后版本

New member reading list

Advanced member reading list

Public Research Tools

People you may want to follow

Other teams

Journals you may submit to

Free libraries

Data resources

Seminars

Machine Learning Book

AI Book