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courses:rg [2015/10/15 10:27]
popel 		courses:rg [2015/10/26 23:38]
popel
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 ^ Oct 19 | Martin Popel | Mark Johnson: [[http://cs.brown.edu/courses/cs195-5/fall2009/docs/lecture_10-27.pdf|A brief introduction to kernel classifiers]], 2009. You can also read [[http://ciml.info/dl/v0_9/ciml-v0_9-ch09.pdf|a chapter from ciml.info]]. [[courses:rg:2014:kernels|Questions]] | ^ Oct 19 | Martin Popel | Mark Johnson: [[http://cs.brown.edu/courses/cs195-5/fall2009/docs/lecture_10-27.pdf|A brief introduction to kernel classifiers]], 2009. You can also read [[http://ciml.info/dl/v0_9/ciml-v0_9-ch09.pdf|a chapter from ciml.info]]. [[courses:rg:2014:kernels|Questions]] |
 ^ Oct 26 | Lukáš Žilka, Milan Straka | hands-on tutorial on using some neural network toolkit | ^ Oct 26 | Lukáš Žilka, Milan Straka | hands-on tutorial on using some neural network toolkit |
-^ Nov  2 |                           | Michael Collins: [[http://ucrel.lancs.ac.uk/acl/W/W02/W02-1001.pdf|Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms]], EMNLP 2002. |+^ Nov  2 |                           | Michael Collins: [[http://ucrel.lancs.ac.uk/acl/W/W02/W02-1001.pdf|Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms]], EMNLP 2002. [[courses:rg:2014:perceptron|Questions]] |
 ^ Nov  9 | —                         | no RG, dean's day | ^ Nov  9 | —                         | no RG, dean's day |
 ^ Nov 16 |                           | Andrew McCallum, Dayne Freitag, Fernando Pereira: [[http://www.ai.mit.edu/courses/6.891-nlp/READINGS/maxent.pdf|Maximum Entropy Markov Models for Information Extraction and Segmentation]], Conference on Machine Learning 2000, [[http://courses.ischool.berkeley.edu/i290-dm/s11/SECURE/gidofalvi.pdf|slides]] | ^ Nov 16 |                           | Andrew McCallum, Dayne Freitag, Fernando Pereira: [[http://www.ai.mit.edu/courses/6.891-nlp/READINGS/maxent.pdf|Maximum Entropy Markov Models for Information Extraction and Segmentation]], Conference on Machine Learning 2000, [[http://courses.ischool.berkeley.edu/i290-dm/s11/SECURE/gidofalvi.pdf|slides]] |

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