Compressing to VC dimension many points

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

Volumn 2777, Issue , 2003, Pages 743-744

  Warmuth, Manfred K ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL GEOMETRY; CONFORMAL MAPPING; DATA COMPRESSION; NUMERICAL METHODS; THEOREM PROVING;

CONJECTURE; HYPOTHESIS; ORTHOGONAL RECTANGLES; SUBSETS;

SET THEORY;

EID: 9444286942     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-540-45167-9_60     Document Type: Conference Paper

References (2)

1. S. Floyd and M. K. Warmuth. Sample compression, learnability, and the Vapnik-Chervonenkis dimension. Machine Learning, 21(3):269-304, 1995.
2. N. Littlestone and M. K. Warmuth. Relating data compression and learnability. Unpublished manuscript, obtainable at http://www.cse.ucsc.edu/ m~anfred, June 10 1986.