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papers:summa-2011 [2011/10/12 21:19]
leonb [Contents] 		papers:summa-2011 [2011/10/12 21:28] (current)
leonb [Statistical Learning and Data Science]
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 ===== Statistical Learning and Data Science ===== ===== Statistical Learning and Data Science =====
  
-**Mireille Gettler Summa, Leon Bottou, Bernard Goldfarb, Fionn Murtagh, Catherine Pardoux, Myriam Touati**, Eds.+Editors: **Mireille Gettler Summa, Léon Bottou, Bernard Goldfarb, Fionn Murtagh, Catherine Pardoux, Myriam Touati**.
  
 {{summa-2011.jpg?150 }} {{summa-2011.jpg?150 }}
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 //**Statistical Learning and Data Science**//, Edited by Mireille Gettler Summa, Léon Bottou, Bernard Goldfarb, Fionn Murtagh, Catherine Pardoux and Myriam Touati, CRC Computer Science & Data Analysis, Chapman & Hall, 2011. //**Statistical Learning and Data Science**//, Edited by Mireille Gettler Summa, Léon Bottou, Bernard Goldfarb, Fionn Murtagh, Catherine Pardoux and Myriam Touati, CRC Computer Science & Data Analysis, Chapman & Hall, 2011.
  
-[[http://www.taylorandfrancis.com/books/details/9781439867631/|Link]]+[[http://www.taylorandfrancis.com/books/details/9781439867631/|Taylor & Francis]] 
 +[[http://www.crcpress.com/product/isbn/9781439867631|CRC Press]] 
 +[[http://www.amazon.com/exec/obidos/ASIN/1439867631/|Amazon]] 
 +[[http://search.barnesandnoble.com/booksearch/isbninquiry.asp?r=1&ean=9781439867631|Barnes & Noble]] 
 </box> </box>
  
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-  ==== Contents ====+==== Contents ====
  
   - Mining on Social Networks.\\ //Benjamin Chapus, Françoise Fogelman Soulié, Erik Marcadé, Julien Sauvage//.   - Mining on Social Networks.\\ //Benjamin Chapus, Françoise Fogelman Soulié, Erik Marcadé, Julien Sauvage//.
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 ==== Notes ==== ==== Notes ====
  
-Chapter 5 (Chervonenkis) contains a short proof that elucidates what happens when the uniform convergence does not take place, that is, when the entropy per example converges to a number //c>0//. It is then possible to identify a subspace of probability //c// on which the learning machine is non-falsifiable. This result has been mentioned in //Statistical Learning Theory// (Vapnik, 1998. theorem 3.6). To my knowledge, this is the first publication of the proof in English.+Chapter 5 (Chervonenkis) contains a short proof that elucidates what happens when the uniform convergence does not take place, that is, when the entropy per example converges to a number //c>0//. It is then possible to identify an event with probability //c// for which the learning machine is non-falsifiable. This result has been mentioned in //Statistical Learning Theory// (Vapnik, 1998. theorem 3.6). To my knowledge, this is the first publication of the proof in English.
  
papers/summa-2011.1318468773.txt.gz · Last modified: 2011/10/12 21:19 by leonb

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