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Publikationsliste

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O

Gaussian Processes for Classification: Mean Field Algorithms [21]

Opper, M. and Winther, O.

Neural Computation, 2655-2684. 2000

Link zur Publikation [22] Download Bibtex Eintrag [23]

Online versus Offline Learning [24]

Opper, M.

Phil. Mag. B, 1531-1537. 1998

Link zur Publikation [25] Download Bibtex Eintrag [26]

Convexity, Internal Representations and the Statistical Mechanics of Neural Networks [27]

Opper, M., Mietzner, A. and Kuhlmann, P.

Europhys. Lett., 31-36. 1997

Link zur Publikation [28] Download Bibtex Eintrag [29]

Online versus Offline Learning from Random Examples: General Results [30]

Opper, M.

Phys. Rev. Lett., 4671-4674. 1996

Link zur Publikation [31] Download Bibtex Eintrag [32]

A mean field approach to Bayes learning in feed–forward neural networks [33]

Opper, M. and Winther, O.

Phys. Rev. Lett., 1964-1967. 1996

Link zur Publikation [34] Download Bibtex Eintrag [35]

M

Maximal Stability in Unsupervised Learning [36]

Mietzner, A., Opper, M. and Kinzel, W.

J. Phys. A, 2785–2797. 1995

Download Bibtex Eintrag [37]

Approximate Analytical Bootstrap Averages for Support Vector Classifiers [38]

Malzahn, D. and Opper, M.

Advances in Neural Information Processing Systems 16. MIT Press. 2004

Link zur Publikation [39] Download Bibtex Eintrag [40]

A Statistical Mechanics Approach to Approximate Analytical Bootstrap Averages [41]

Malzahn, D. and Opper, M.

Advances in Neural Information Processing Systems 15. MIT Press, 327-334. 2003

Link zur Publikation [42] Download Bibtex Eintrag [43]

A Variational Approach to Learning Curves [44]

Malzahn, D. and Opper, M.

Advances in Neural Information Processing Systems 14. MIT Press, 463-469. 2002

Link zur Publikation [45] Download Bibtex Eintrag [46]

Learning curves for Gaussian processes models: Fluctuations and Universality [47]

Malzahn, D. and Opper, M.

Proceedings of the International Conference on Artificial Neural Networks 2001. Springer–Verlag, 271-276. 2001

Link zur Publikation [48] Download Bibtex Eintrag [49]

Learning Curves for Gaussian processes regression: A framework for good approximations [50]

Malzahn, D. and Opper, M.

Advances in Neural Information Processing Systems 13. MIT Press, 273-279. 2001

Link zur Publikation [51] Download Bibtex Eintrag [52]

A statistical physics approach for the analysis of machine learning algorithms on real data [53]

Malzahn, D. and Opper, M.

Journal of Statistical Mechanics (JSTAT) 2005

Link zur Publikation [54] Download Bibtex Eintrag [55]

An Approximate Analytical Approach to Resampling Averages [56]

Malzahn, D. and Opper, M.

Journal of Machine Learning Research, 1151–1173. 2003

Link zur Publikation [57] Download Bibtex Eintrag [58]

Learning Curves and Bootstrap Estimates for Inference with Gaussian Processes: A Statistical Mechanics Study [59]

Malzahn, D. and Opper, M.

Complexity, 57-63. 2003

Link zur Publikation [60] Download Bibtex Eintrag [61]

Statistical Mechanics of Learning: A Variational Approach for Real Data [62]

Malzahn, D. and Opper, M.

Phys. Rev. Lett., 108302.1-108302.4. 2002

Link zur Publikation [63] Download Bibtex Eintrag [64]

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