Classic methods of Machine Learning
STAT 592 / CSE 590 MM Winter Quarter 2004

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Course notes and reading

  • Maximum entropy course notes
  • Boosting
    • On Boosting

      • Y. Freund, "Boosting a weak learning algorithm by majority", Information and Computation, 9:1545-1588, 1997.
      • Y. Freund, and R. Schapire, "Experiments with a new boosting algorithm", in Machine Learning: Proceedings of the Thirteenth International Conference, pp. 148-156, 1996.
      • R. Schapire, Y. Freund, P. Bartlett, and W. S. Lee, "Boosting the margin: a new explanation for the effectiveness of voting methods", in Machine Learning: Proceedings of the Fourteenth Interbational Conference, 1997.
      • J. Friedman, T. hastie, and R. Tibshirani, "Additive logistic regression: a statistical view of boosting", Annals of Statistics, 2000.
      • H. Drucker, and C. Cortes, "Boosting decision trees", in Advances in Neural Information Processing Systems 8, pp. 479-485, 1996.
    • On Error Bounds, and combining classifiers

      • V. Koltchinskii, D. Panchenko, "Some new bounds on the generalization error of combined classifiers", NIPS 2000, pp. 245-251.
      • A. Murua, "Upper bounds for error rates associated to linear combination of classifiers", IEEE PAMI, May 2002.
      • E. Bauer, and R. Kohavi, "An empirical comparison of voting classification algorithms: bagging, boosting, and variants", Machine Learning, 36, 105-142, 1999.
    • On Bagging, Arcing, and Random Forests

      • Y. Amit, and A. Murua, "Speech recognition using randomized relational decision trees", IEEE, Trans. Speech and Audio Processing, 9, May 2001.
      • Y. Amit, and D. Geman, "Shape quantization and recognition with randomized trees", Neural Computation 9, pp. 1545-1588, 1997.
      • L. Breiman, "Bagging predictors", Machine Learning, 24(2):123-140, 1996.
      • L. Breiman, "RF/TOOLS: A Class of Two-eyed Algorithms", SIAM Workshop, May 2003, Statistics Department, UCB.
      • L. Breiman, "Random Forests", 2001, Statistics Department, UCB.
      • L. Breiman, "Prediction games and arcing algorithms", Statistics Department, UCB.
  • Dimension reduction