Unlabeled compression schemes for maximum classes

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3559 LNAI, Issue , 2005, Pages 591-605

  Kuzmin, Dima ^a   Warmuth, Manfred K ^a  

^a University of California Santa Cruz   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); LEARNING SYSTEMS;

COMPRESSION SCHEMES; VC DIMENSION;

DATA COMPRESSION;

EID: 26944445402     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11503415_40     Document Type: Conference Paper

References (16)

1. [Flo89] S. Floyd. Space-bounded learning and the Vapnik-Chervonenkis Dimension (Ph.D). PhD thesis, U.C. Berkeley, December 1989. ICSI Tech Report TR-89-061.
2. [FW95] S. Floyd and M. K. Warmuth. Sample compression, learnability, and the Vapnik-Chervonenkis dimension. Machine Learning, 21(3):269-304, 1995.
3. [Gur97] Leonid Gurvits. Linear algebraic proofs of VC-dimension based inequalities. In Shai Ben-David, editor, EuroCOLT '97, Jerusalem, Israel, March 1997, pages 238-250. Springer Verlag, March 1997.
4. [HLW94] D. Haussler, N. Littlestone, and M. K. Warmuth. Predicting {0,1} functions on randomly drawn points. Information and Computation, 115(2):284-293, 1994. Was in FOCS88, COLT88, and Univ. of California at Santa Cruz TR UCSC-CRL-90-54.
5. [Lan03] John Langford. Tutorial on practical prediction theory for classification. ICML, 2003.
6. [LLS02] Y. Li, P. M. Long, and A. Srinivasan. The one-inclusion graph algorithm is near optimal for the prediction model of learning. Transaction on Information Theory, 47(3):1257-1261, 2002.
7. [LW86] N. Littlestone and M. K. Warmuth. Relating data compression and learnability. Unpublished manuscript, obtainable at http://www.cse.ucsc.edu/ ~manfred, June 10 1986.
8. [MST02] Mario Marchand and John Shawe-Taylor. The Set Covering Machine. Journal of Machine Learning Research, 3:723-746, 2002.
9. [MST03] Mario Marchand and John Shawe-Taylor. The Decision List Machine. In Advances in Neural Information Processing Systems 15, pages 921-928. MIT-Press, Cambridge, MA, USA, 2003.
10. [Sau72] N. Sauer. On the density of families of sets. Journal of Combinatorial Theory (A), 13:145-147, 1972.
11. [Vap82] V. N. Vapnik. Estimation of Dependences Based on Empirical Data. Springer-Verlag, New York, 1982.
12. [VC71] V. N. Vapnik and A. Y. Chervonenkis. On the uniform convergence of relative frequencies of events to their probabilities. Theory of Probab. and its Applications, 16(2):264-280, 1971.
13. [vLBS04] Ulrike von Luxburg, Olivier Bousquet, and Bernard Schölkopf. A compression approach to support vector model selection. Journal of Machine Learning Research, 5(Apr):293-323, 2004.
14. [War03] M. K. Warmuth. Compressing to VC dimension many points. COLT open problems, 2003.
15. [War04] M. K. Warmuth. The optimal PAC algorithm. COLT open problems, 2004.
16. [Wel87] E. Welzl. Complete range spaces. Unpublished notes, 1987.