[Todos] ECI: Curso de Alon Orlitsky

[Ana Ruedin]

Están cordialmente invitados a asistir al curso:
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*Theory and applications of universal data compression and probability 
estimation*
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que dictará el Profesor Alon Orlitsky, ECE Department, University of 
California, San Diego, USA,

_ <http://kodiak.ucsd.edu/alon/>_en el marco de la Escuela de Ciencias 
Informáticas, ECI.

El curso abarcará la estimación de eventos de baja probabilidad, entre 
otros temas.

Lugar: Pabellón I Ciudad Universitaria, Departamento de Computación.
Fechas: del 28 de julio al 2 de agosto 2008.
Horario: de 14 a 17 hrs.
Duración del curso: 15 horas.
Idioma: inglés.
Arancel para alumnos y docentes de instuciones nacionals provinciales o 
estatales: 50$.

Program:
The class covers the theory and applications of universal data 
compression, and explores their relation to probability estimation. No 
prior knowledge is assumed and the material ranges from standard 
textbook to ongoing research.
Time permitting, topics will include:

- Compression and its entropy limit. Standard compression algorithms 
such as Shannon, Huffman, and arithmetic coding. Showing that they 
compress certain information processes to their entropy.

- Challenges arising when the underlying distribution is unknown, for 
example when compressing text or images. The universal compression 
approach. Commonly used universal compression algorithms such as 
Krichevsky-Trofimov and Lempel-Ziv. Their optimality.

- The necessity to compress data over large alphabets. The effect of 
alphabet size on compression performance. Techniques for data 
compression over large alphabets.

- The relation between universal compression and probability estimation. 
Estimation of low- probability events, population sizes, and the number 
of species. The Good-Turing estimator.

- The relation between universal compression and investment portfolio 
theory.

- Relations to combinatorial topics such as the Bell and Stirling 
numbers and to Hardy and Ramanujan’s seminal work on the number of 
partitions.

*Bibliografía*

   1. P.S. Laplace. Philosphical essays on probabilities. Springer
      Verlag, New York.
   2. G.H. Hardy and S. Ramanujan. Asymptotic formulae in combinatory
      analysis. Proceedings of London Mathematics Society, 17(2):75–115,
      1918.
   3. R. Fisher, A. Corbet, and C. Williams. The relation between the
      number of species and the number of individuals in a random sample
      of an animal population. jae, 12:42–48, 1943.
   4. C.E. Shannon. A mathematical theory of communication. Bell Systems
      Technical Journal, 27:379–423, 623–656, 1948. I.J. Good. The
      population frequencies of species and the estimation of population
      parameters. Biometrika, 40(3/4):237–264, December 1953.
   5. J. Rissanen. Universal coding, information, prediction, and
      estimation. IEEE Trans. on Information Theory, 30(4):629–636, July
      1984.
   6. R. Thisted and B. Efron. Did shakespeare write a newlydiscovered
      poem? Biometrika, 74:445–455, 1987.
   7. T. Cover and J. Thomas. Elements of Information Theory. John Wiley
      and sons., 1991.
   8. T.M. Cover. Universal portfolios. Mathematical Finance, 1(1):1–29,
      January 1991.
   9. A. Orlitsky, N.P. Santhanam, and J. Zhang. Always Good Turing:
      Asymptotically optimal probability estimation. Science,
      302(5644):427–431, October 17 2003.
  10. A. Orlitsky, N.P. Santhanam, and J. Zhang. Universal compression
      of memoryless sources over unknown alphabets. IEEE Trans. on
      Information Theory, 50(7):1469–1481, July 2004.


    Profesor:

    * Alon Orlitsky <http://kodiak.ucsd.edu/alon/>, ECE Department,
      University of California, San Diego, USA.

      Alon Orlitsky joined the UCSD faculty in 1997, after a two-year
      stint as a quantitative analyst with D.E. Shaw & Company. From
      1986-1996, he was a member of the technical staff at AT&T Bell
      Labs' Mathematical Sciences Research Center. Orlitsky received his
      Ph.D. in Electrical Engineering from Stanford University in 1986,
      and his M.Sc., also from Stanford, in 1982. He did his
      undergraduate work in mathematics (B.Sc. 1980) and Electrical
      Engineering (B.Sc. 1981) at Israel's Ben-Gurion University. His
      honors include an ITT International Fellowship in 1982, and an
      IEEE W.R.G. Baker best-paper award in 1992. Orlitsky co-edited a
      book on "Theoretical advances in neural computation and learning".

Más información:
http://www.dc.uba.ar/events/eci/2008/courses/t1/
http://www.dc.uba.ar/events/eci/2008/




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Dra. Ana Ruedin
Departamento de Computación
Facultad de Ciencias Exactas y Naturales
Universidad de Buenos Aires


Ciudad Universitaria, Pabellón I, E.P.
(C1428EGA) Buenos Aires. Argentina.
Tel.: +54-11-4576-3390/96 int 719
Fax: +54-11-4576-3359.

e-mail: ana.ruedin en dc.uba.ar