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M

Linear approaches to a stochastic mechanical control problem [21]

Mabrouk, M.

2010 TU Berlin

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

Common Input Explains Higher-Order Correlations and Entropy in a Simple Model of Neural Population Activity [24]

Macke, J., Opper, M. and Bethge, M.

Physical Review Letters. American Physical Society, 208102. 2011

Download Bibtex Eintrag [25]

Approximate Analytical Bootstrap Averages for Support Vector Classifiers [26]

Malzahn, D. and Opper, M.

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

Link zur Publikation [27] Download Bibtex Eintrag [28]

A Statistical Mechanics Approach to Approximate Analytical Bootstrap Averages [29]

Malzahn, D. and Opper, M.

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

Link zur Publikation [30] Download Bibtex Eintrag [31]

A Variational Approach to Learning Curves [32]

Malzahn, D. and Opper, M.

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

Link zur Publikation [33] Download Bibtex Eintrag [34]

Learning curves for Gaussian processes models: Fluctuations and Universality [35]

Malzahn, D. and Opper, M.

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

Link zur Publikation [36] Download Bibtex Eintrag [37]

Learning Curves for Gaussian processes regression: A framework for good approximations [38]

Malzahn, D. and Opper, M.

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

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

A statistical physics approach for the analysis of machine learning algorithms on real data [41]

Malzahn, D. and Opper, M.

Journal of Statistical Mechanics (JSTAT) 2005

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

An Approximate Analytical Approach to Resampling Averages [44]

Malzahn, D. and Opper, M.

Journal of Machine Learning Research, 1151–1173. 2003

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

Learning Curves and Bootstrap Estimates for Inference with Gaussian Processes: A Statistical Mechanics Study [47]

Malzahn, D. and Opper, M.

Complexity, 57-63. 2003

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

Statistical Mechanics of Learning: A Variational Approach for Real Data [50]

Malzahn, D. and Opper, M.

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

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

Maximal Stability in Unsupervised Learning [53]

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

J. Phys. A, 2785–2797. 1995

Download Bibtex Eintrag [54]

O

Bounds for Predictive Errors in the Statistical Mechanics of Supervised Learning [55]

Opper, M. and Haussler, D.

Phys. Rev. Lett., 3772-3775. 1995

Link zur Publikation [56] Download Bibtex Eintrag [57]

Statistical Physics Estimates for the Complexity of Feedworward Neural Networks [58]

Opper, M.

Phys. Rev E, 3613–3618. 1995

Download Bibtex Eintrag [59]

Learning and Generalization in a Two–Layer Neural Network: The Role of the Vapnik–Chervonenkis–Dimension [60]

Opper, M.

Phys. Rev. Lett., 2113–2116. 1994

Download Bibtex Eintrag [61]

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