Difference between revisions of "Lecture Materials"

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* Classification [ [http://www.csd.uwo.ca/~dlizotte/teaching/cs4414_F17/Lectures/7_Classification/classification.html slides] | [http://www.csd.uwo.ca/~dlizotte/teaching/cs4414_F17/Lectures/7_Classification/classification.Rmd Rmd] | [http://www.csd.uwo.ca/~dlizotte/teaching/cs4414_F17/Lectures/7_Classification/classification.pdf pdf]]
 
* Classification [ [http://www.csd.uwo.ca/~dlizotte/teaching/cs4414_F17/Lectures/7_Classification/classification.html slides] | [http://www.csd.uwo.ca/~dlizotte/teaching/cs4414_F17/Lectures/7_Classification/classification.Rmd Rmd] | [http://www.csd.uwo.ca/~dlizotte/teaching/cs4414_F17/Lectures/7_Classification/classification.pdf pdf]]
 
* Nonlinear Models [ [http://www.csd.uwo.ca/~dlizotte/teaching/cs4414_F17/Lectures/8_Nonlinear%20Models/nonlinear_models.html slides] | [http://www.csd.uwo.ca/~dlizotte/teaching/cs4414_F17/Lectures/8_Nonlinear%20Models/nonlinear_models.Rmd Rmd] | [http://www.csd.uwo.ca/~dlizotte/teaching/cs4414_F17/Lectures/8_Nonlinear%20Models/nonlinear_models.pdf pdf] ]
 
* Nonlinear Models [ [http://www.csd.uwo.ca/~dlizotte/teaching/cs4414_F17/Lectures/8_Nonlinear%20Models/nonlinear_models.html slides] | [http://www.csd.uwo.ca/~dlizotte/teaching/cs4414_F17/Lectures/8_Nonlinear%20Models/nonlinear_models.Rmd Rmd] | [http://www.csd.uwo.ca/~dlizotte/teaching/cs4414_F17/Lectures/8_Nonlinear%20Models/nonlinear_models.pdf pdf] ]
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* Unsupervised Learning [ [http://www.csd.uwo.ca/~dlizotte/teaching/cs4414_F17/Lectures/9_Unsupervised%20Learning/unsupervised-learning.html slides] | [http://www.csd.uwo.ca/~dlizotte/teaching/cs4414_F17/Lectures/9_Unsupervised%20Learning/unsupervised-learning.Rmd Rmd] | [http://www.csd.uwo.ca/~dlizotte/teaching/cs4414_F17/Lectures/9_Unsupervised%20Learning/unsupervised-learning.pdf pdf] ]
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'''Materials with associated video lectures (see OWL)'''
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* Classification Performance Evaluation [ [http://www.csd.uwo.ca/~dlizotte/teaching/cs4414_F17/Lectures/10_Classification%20Performance%20Evaluation/classification_performance_evaluation.html slides] | [http://www.csd.uwo.ca/~dlizotte/teaching/cs4414_F17/Lectures/10_Classification%20Performance%20Evaluation/classification_performance_evaluation.Rmd Rmd] | [http://www.csd.uwo.ca/~dlizotte/teaching/cs4414_F17/Lectures/10_Classification%20Performance%20Evaluation/classification_performance_evaluation.pdf pdf] ]
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= Previous Offerings =
 
= Previous Offerings =
  

Latest revision as of 21:58, 24 November 2017

Lecture Materials

Materials from the most recent run of the course will be posted here. They will be updated as the term progresses.

Materials with associated video lectures (see OWL)

  • Classification Performance Evaluation [ slides | Rmd | pdf ]


Previous Offerings

From W17

  • Information Visualisation
  • Lecture on what I would call "Principles of Information Visualisation"
  • Inspiration from the Tableau public gallery. (Recall Tableau is free for students.)


From W16

  • Flu trends papers: On OWL

Tutorials and Summaries

Other Resources

  • Bibliography/suggested reading from Colin Cherry's lecture:
    • Structured Perceptron
      • Michael Collins. Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms. EMNLP 2002. [1]
    • Some applications:
      • Scott Miller; Jethran Guinness; Alex Zamanian. Name Tagging with Word Clusters and Discriminative Training. NAACL 2004. [2]
      • Robert C. Moore. A Discriminative Framework for Bilingual Word Alignment. EMNLP 2005. [3]
    • Passive Aggressive Algorithm and MIRA:
      • Koby Crammer and Yoram Singer. Ultraconservative Online Algorithms for Multiclass Problems. Journal of Machine Learning Research 2003. [4]
      • Koby Crammer, Ofer Dekel, Joseph Keshet, Shai Shalev-Shwartz, Yoram Singer. Online Passive-Aggressive Algorithms. Journal of Machine Learning Research 2006. [5]
    • Applications (of MIRA):
      • Ryan McDonald; Koby Crammer; Fernando Pereira Online Large-Margin Training of Dependency Parsers. ACL 2005. [6]
      • Sittichai Jiampojamarn; Colin Cherry; Grzegorz Kondrak. Joint Processing and Discriminative Training for Letter-to-Phoneme Conversion. ACL 2008. [7]
    • Pegasos
      • Shai Shalev-Shwartz, Yoram Singer, and Nathan Srebro. Pegasos: Primal Estimated sub-GrAdient SOlver for SVM. ICML 2007. [8]
    • Structured SVM:
      • I. Tsochantaridis, T. Hofmann, T. Joachims, and Y. Altun. Support Vector Learning for Interdependent and Structured Output Spaces. ICML 2004. [9]
      • B. Taskar, C. Guestrin and D. Koller. Max-Margin Markov Networks. Neural Information Processing Systems Conference [10]

Previous Incarnations of This Course: CS886 at the University of Waterloo

S13

EarlierTerms