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Extension of the PAC framework to finite and countable Markov chains
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Source Annual Workshop on Computational Learning Theory archive
Proceedings of the twelfth annual conference on Computational learning theory table of contents
Santa Cruz, California, United States
Pages: 308 - 317  
Year of Publication: 1999
ISBN:1-58113-167-4
Author
David Gamarnik  IBM T.J. Watson Research Center, PO Box 218, Yorktown Heights, NY
Sponsors
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGART: ACM Special Interest Group on Artificial Intelligence
Univ. of California, : University of California at Santa Cruz
Publisher
ACM  New York, NY, USA
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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
D. Aldous and J. Fill. Reversible Markov Chains and Random Walks on Graphs. In preparation.
 
2
D. Aidous and U. ~3.zirani. A Markovian extension of Valiant's learning model. Proc. 31st Symposium on 1990.
 
3
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D. Bertsimas, D. Gamarnik, and J. Tsitsiklis. Geometric bounds for stationary distribution of infinite Markov Chains via Lyapunov functions. Preprint, i 998.
 
6
K.L. Buescher and P.R. Kumar. Learning by canoni- 1EEE Transactions on Automatic Control, 41:545-556, 1996.
 
7
K.L. Buescher and P.R. Kumar. Learning by canonical smooth estimation, part II: Learning and model complexity. IEEE Transactions on Automatic Control, 41:557-569, 1996.
 
8
P. Diaconis, R. Graham, and J. Morrison. Asymptotic analysis of a random walk on a hypercube with many dimensions. Random Structures and Aigorithms, 1:51- 72, 1990.
 
9
 
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S.P. Meyn. Computable bounds for geometric convergence rates of markov chains. Ann. ofAppl." ' ' rrou., ~, 1994.
 
13
S.P. Meyn and R.L. Tweedie. MArkov Chains and Stochastie Stability. Springer-~erlag, 1993.
 
14
A. Nobel. A counterexample concerning uniform ergodic theorems for a class of functions. Statistics and Probability Letters, 24:165-168, 1995.
 
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