Reading Assignment 2
Here are four different papers dealing with support vector machines
and ensembles of classifiers. You have to choose one of these
papers, read it and write a short summary (maximum two pages, 12
point font). Your summary should contain the following points (not
necessarily in this order):
- The main idea expressed in the paper
- The theoretical justification
of the idea
- Empirical support provided by the experiments in the
- What you liked or disliked about the paper
- Questions you had about the paper, aspects you did not understand
You should bring your summary to class on Tuesday, November 12.
Be prepared to shortly summarize the paper in front of your colleagues
and participate in discussion.
The papers for this reading assignment are:
T. Joachims. (1998). "Text categorization with support vector machines: Learning with many relevant features". In Claire NÚdellec and CÚline
Rouveirol, editors, Proceedings of the European Conference on Machine Learning, pages 137-142, Springer.
M. Pontil and A. Verri. (1998).
"Support Vector Machines for 3D Object Recognition".
IEEE Trans. on PAMI, Vol. 20, No. 6, pp 637-646.
T. G. Dietterich. (2000).
An experimental comparison of three methods for
constructing ensembles of decision trees: Bagging, boosting, and
randomization. In Machine Learning, 40(2):139-158.
L. Breiman (1996). Bias, variance, and arcing classifiers Technical Report 460, Statistics Department, University of California.
Prof. Doina PRECUP
Last modified: Wed Sep 18 20:21:07 EDT 2002