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COGS 202 SPRING 2011    Mon  1pm  CSB 003

 DATE     TOPIC             
 SLIDES 
 READING                   
 MAR 28
 Computational Neuroscience
 bootcampcompout.pdf                                                                                                 
 APR 4
 History and Intro to Neural Networks
 backpropnotes.pdfChapter 5 of Bishop Pattern Recognition and Machine Learning OR
(less advanced)
Chapter 8 of Parallel Distributed Processing Vol 1 (blue book)

 APR 11
 Training Issues and Overfitting
cont'd from above
 
 APR 18
 Multi-task learning
 inpsandouts.pdf http://www.cs.cornell.edu/~caruana/mlj97.pdf
http://www.cogsci.ucsd.edu/academicPubs/desa/variableselection.pdf
 APR 25
                                           Higher level Bayesian modeling           
                                                                  
 
http://www.cns.nyu.edu/ftp/lcv/weiss02-preprint.pdf
 MAY 2
 SVMs  http://see.stanford.edu/materials/aimlcs229/cs229-notes3.pdf
MAY 9
 special architectures in neural networks
 http://yann.lecun.com/exdb/publis/index.html#bengio-lecun-07.pdf


    
 MAY 16
starting at 2PM
self-supervised learning
  One of the below papers
http://www.cogsci.ucsd.edu/academicPubs/desa/segregation.pdf
http://www.cogsci.ucsd.edu/academicPub/desa/categorylearning.pdf
http://www.cogsci.ucsd.edu/academicPubs/desa/perceptchap.pdf
 MAY 23
 starting at 1:30PM data analysis
  
 MAY 30 
 MEMORIAL
 DAY
 NO CLASS