Scale-sensitive dimensions, uniform convergence, and learnability

Journal of the ACM

Volumn 44, Issue 4, 1997, Pages 615-631

  Alon, Noga ^a   Ben David, Shai ^b   Cesa Bianchi, Nicolò ^c   Haussler, David ^d,e  

^a TEL AVIV UNIVERSITY   (Israel)

^b TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

^c UNIVERSITY OF MILAN   (Italy)

^d UNIVERSITY OF CALIFORNIA   (United States)

^e University of California Santa Cruz   (United States)

Author keywords

PAC learning; Theory; Uniform laws of large numbers; Vapnik Chervonenkis dimension

Indexed keywords

CONVERGENCE OF NUMERICAL METHODS; FUNCTIONS; MATHEMATICAL MODELS; NUMBER THEORY; PROBABILITY; RANDOM PROCESSES; REGRESSION ANALYSIS; THEOREM PROVING;

UNIFORM GLIVENKO CANTELLI CLASSES; VAPNIK CHERVONENKIS DIMENSIONS;

LEARNING SYSTEMS;

EID: 0031176507     PISSN: 00045411     EISSN: None     Source Type: Journal    
DOI: 10.1145/263867.263927     Document Type: Article

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