Extension of the PAC framework to finite and countable Markov chains

Proceedings of the Annual ACM Conference on Computational Learning Theory

Volumn , Issue , 1999, Pages 308-317

  Gamarnik, David ^a  

^a IBM T J WATSON RESEARCH CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; EIGENVALUES AND EIGENFUNCTIONS; FUNCTIONS; LYAPUNOV METHODS; MARKOV PROCESSES; MATHEMATICAL MODELS; MATRIX ALGEBRA; POLYNOMIALS; SET THEORY;

LYAPUNOV FUNCTION TECHNIQUE; MARKOV CHAIN; PROBABLY APPROXIMATELY CORRECT LEARNING; UNIFORM STATIONARY DISTRIBUTION;

LEARNING SYSTEMS;

EID: 0033281292     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/307400.307478     Document Type: Conference Paper

References (15)