Lecture Materials

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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