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courses:rg [2016/10/04 15:42]
popel 		courses:rg [2016/10/06 08:54]
popel
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 === Autumn&Winter 2016/2017 === === Autumn&Winter 2016/2017 ===
 ^ date   | **speaker**               | **paper** | ^ date   | **speaker**               | **paper** |
-^ Oct  4 |   | startup meeting |  +^ Oct  4 |   | startup meeting | 
-^ Oct 11 |   | Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu: [[http://aclweb.org/anthology-new/P/P02/P02-1040.pdf|BLEU: a Method for Automatic Evaluation of Machine Translation]], ACL 2002. [[courses:rg:2014:bleu|Questions]] | +^ Oct 11 | Martin Popel | Kevin Knight, Beáta Megyesi and Christiane Schaefer: [[http://www.isi.edu/natural-language/people/copiale-11.pdf|The Copiale Cipher]], BUCC 2011, you can watch a [[https://www.youtube.com/watch?v=Eam0Tk-1FyI|trailer]] | 
-^ Oct 18 |  | 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]]| +^ Oct 18 | Daniela Bodanská  | Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu: [[http://aclweb.org/anthology-new/P/P02/P02-1040.pdf|BLEU: a Method for Automatic Evaluation of Machine Translation]], ACL 2002. [[courses:rg:2014:bleu|Questions]] | 
-^ Oct 25  |  | 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]] [[courses:rg:2014:memm|Question]]| +^ Oct 25 |  | 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 1  |  | John Lafferty, Andrew McCallum, Fernando Pereira: [[http://www.cs.utah.edu/~piyush/teaching/crf.pdf|Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data]], 2001. [[courses:rg:2014:crf|Questions]] |+^ Nov 1  |  | 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]] [[courses:rg:2014:memm|Question]]|
 ^ <del>Nov 8</del> | --- | no RG (Dean's day)| ^ <del>Nov 8</del> | --- | no RG (Dean's day)|
-^ Nov 15 |  | Tomas Mikolov, Kai Chen, Greg Corrado, Jeffrey Dean: [[http://arxiv.org/pdf/1301.3781.pdf|Efficient Estimation of Word Representations in Vector Space]], ICLR 2013 | +^ Nov 15 |  | John Lafferty, Andrew McCallum, Fernando Pereira: [[http://www.cs.utah.edu/~piyush/teaching/crf.pdf|Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data]], 2001. [[courses:rg:2014:crf|Questions]] | 
-^ Nov 22  |  | |+^ Nov 22 |  | Tomas Mikolov, Kai Chen, Greg Corrado, Jeffrey Dean: [[http://arxiv.org/pdf/1301.3781.pdf|Efficient Estimation of Word Representations in Vector Space]], ICLR 2013 | 
 +^ Nov 29  |  | |
 ^ Dec 6  |  | | ^ Dec 6  |  | |
 ^ Dec 13 |  | | ^ Dec 13 |  | |

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