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Randomized approximate aggregating strategies and their applications to prediction and discrimination

Published: 05 July 1995 Publication History
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    References

    [1]
    Chan~ K.S.(1993)4 Asymptotic behavior of the Gibbs sampler. Jr~ American Statist. Assoc, 88~ 421:320-326o
    [2]
    Clarke, B. and Barron, A.(1990). Information-theoretic asymptotics of Bayes methods, IEEE Trans~ Inform. Theory, IT-36,453-471o
    [3]
    Dawid, A.(1984). Statistical theory: the presequential approach. J. R. Stat. S,c. A, 278-292.
    [4]
    Gelfand~ A.E. and Smith, A.F.M.(1990). Samplingbased approach to calculating marginal densities. J.Am. Statist. Assoc., 85:398-409.
    [5]
    Geman, S. and Geman, D.(1984) Stochastic relaxation, Gibbs distributions, and the Bayes restoration of images. IEEE Trans. on Pattern Analysis and Machine Intelligence, PAMI-6, 721-741.
    [6]
    Hastings, W.K.(1970). Monte Carlo sampling method using Markov chains and their applications. Biometrika, 57: 97-109.
    [7]
    Kivinen, J. and Warmuth, M.(1993). Using experts for predicting continuous outcomes. In Computational Learning Theory: EuroCOLT'9S, (pp.109-120), Oxford.
    [8]
    Metropolis, N., Rosenbluth, M.N., Rosenbluth, A.H., Teller, A.H., Teller, E.(1953). Equations of state calculations by fast computation machines. J. Chemical Physics, 21:1087-1091.
    [9]
    Rissanen, J.(1989). Stochastic Complexity in Statistical fnqmry, World Scientific~
    [10]
    Robert,G.O. and Polson N.G.(1994). On the geometric convergence of the Gibbs sampler~ J.R.Statist. S,c. B~ 56, 2:377-384.
    [11]
    Rosenthal, J.(1993)o Minorization conditions and convergence rates for Markov chain Monte Carlo. Technical report No.9321~ Univ. of Toronto, Dept. of Statistics.
    [12]
    Rosenthal, J.(1994). Analysis of the Gibbs sampler for a model related to James-Stein estimators. Technical report No.9413, Univ. of Toronto, Dept. of Statistics.
    [13]
    Tanner, M.A. and Wong, I-I.Wo(1987)~ The calculation of posterior distributions by data augmentation. Jr. American Statist. Assoc., 82, 528-550.
    [14]
    Tierney, L.(1991). Exploring posterior distributions using Markov chains. In Proc. of 23rd Symp~ on the Interface, (pp.563-570).
    [15]
    Vovk, V.G.(1990). Aggregating Strategies. Proceedings of the Third Annual Workshop on Computational Learning Theory, (pp.371-386), Morgan Kaufmann.
    [16]
    Vovk, V.G.(1995). A game of prediction with expert advice. In Proc. COLT'95.
    [17]
    Yamanishi, K.(1991). A loss bound model for on-line stochastic prediction strategies. In Proc. of COLT'91~ (pp. 290-302), Morgan Kaufmann.
    [18]
    Yamanishi, K.(1995). Probably almost discriminative learning. Machine Learning, 18:23-50, Kluwer Academic Publishers.
    [19]
    Yamanishi, K.(1994). Generalized stochastic complexity and its applications to learning. Proc. of CISSgJ, pp.763-768.
    [20]
    Ziv, J.(1988). On classification with empirically observed statistics and universal data compression. IEEE Trans. IT, IT-34:278-286.

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    cover image ACM Conferences
    COLT '95: Proceedings of the eighth annual conference on Computational learning theory
    July 1995
    464 pages
    ISBN:0897917235
    DOI:10.1145/225298
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    Published: 05 July 1995

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