| Office:
231 Rush Building |
| Tel(O): (215)895-6360 |
| Tel(C): (215)840-6193 |
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Seminar: Information Theory
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| In this semniar, I read the following papers or articles. |
- Claude E. Shannon's Information Theory Paper
C. E. Shannon, "A
mathematical theory of communication", Bell System
Technical Journal, vol. 27, pp. 379-423 and 623-656, July and
October, 1948.
- A Lecture
Notes for Information Theory.
- A Tutorial for Memory Based Learning which use information
theory to weigh each feature.
Walter Daelemans et al., TiMBL:
Tilburg Memory Based Learner V2.0 Reference Guide, ILK Technical
Report- ILK 99-01.
- Maximum Entropy Methodology Paper
A. Berger, S. A. Della Pietra, and V. J. Della Pietra, "A
maximum entropy approach to natural language processing",
Computational Linguistics, vol. 22, pp. 39-71, 1996. Presentation
- Quinlan's ID3 Algorithm for building of Decision Tree.
Quinlan, J.R., "Induction of Decision Trees", Machine Learning,
1986, No.1, pp.81-106.
- Quinlan's C4.5 Algorithm which is an extension to ID3.for
building of Decision Tree.
Quinlan,J.R.: C4.5: Programs for Machine Learning Morgan Kauffman,
1993.
(An
tutorial for ID3 and C4.5)
- Information Network which is similar to but different from
ID3 algorithm.
M. Last, O. Maimon, ¡°A compact and accurate model
for classification¡±, IEEE Transactions on Knowledge
and Data Engineering, Volume 16, Issue 2 , Pages: 203 ¨C
215, 2004.
A Short Presentation for
Information Theory by Myself
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