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List of Publications

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The Complexity of Learning with Supportvector Machines - A Statistical Physics Study [21]

Opper, M.

Adaptivity and Learning. Springer Verlag, 101-108. 2003

Link to publication [22] Download Bibtex entry [23]

Statistical Mechanics of Generalization [24]

Opper, M.

The Handbook of Brain Theory and Neural Networks, 2nd edition. MIT Press, 1087-1090. 2003

Link to publication [25] Download Bibtex entry [26]

Learning to Generalize [27]

Opper, M.

Frontiers of Life. Academic Press, 763-775. 2001

Link to publication [28] Download Bibtex entry [29]

Adaptive TAP Equations [30]

Opper, M. and Winther, O.

Advanced Mean Field Methods: Theory and Practice. MIT Press, 85-97. 2001

Link to publication [31] Download Bibtex entry [32]

From Naive Mean Field Theory to the TAP Equations [33]

Opper, M. and Winther, O.

Advanced Mean Field Methods: Theory and Practice. MIT Press, 7-20. 2001

Link to publication [34] Download Bibtex entry [35]

Imparare a Generalizzare (Learning to Generalize) [36]

Opper, M.

Frontiere della Biologia. Istituto della Enciclopedia Italiana Treccani, 717-729. 2000

Download Bibtex entry [37]

Gaussian Processes and SVM: Mean Field Results and Leave-One-Out [38]

Opper, M. and Winther, O.

Advances in Large Margin Classifiers. MIT Press, 311–326. 2000

Download Bibtex entry [39]

Worst Case Prediction over Sequences under Log Loss [40]

Opper, M. and Haussler, D.

The IMA Volumes in Mathematics and Its Applications, Volume 107: The Mathematics of Information Coding, Extraction & Distribution. Springer Verlag, 81-90. 1999

Link to publication [41] Download Bibtex entry [42]

On the Annealed VC Entropy for Margin Classifiers: A Statistical Mechanics Study [43]

Opper, M.

Advances in Kernel Methods. MIT Press, 117-126. 1998

Link to publication [44] Download Bibtex entry [45]

A Bayesian Approach to Online Learning [46]

Opper, M.

Online Learning in Neural Networks. Cambridge University Press, 363-378. 1998

Link to publication [47] Download Bibtex entry [48]

Regression with Gaussian Processes: Average Case Performance [49]

Opper, M.

Hong Kong International Workshop on Theoretical Aspects of Neural Computation: A Multi-disciplinary Perspective (TANC 97). World Scientific. 1997

Link to publication [50] Download Bibtex entry [51]

Physics of Generalization [52]

Opper, M. and Kinzel, W.

Physics of Neural Networks III. by Springer Verlag, 151–209. 1996

Download Bibtex entry [53]

General Bounds for Predictive Errors in Supervised Learning [54]

Opper, M. and Haussler, D.

Theory of Neural Networks, The Statistical Mechanics Perspective. World Scientific, 51-58. 1995

Link to publication [55] Download Bibtex entry [56]

Statistical Mechanics of Learning: Generalization [57]

Opper, M.

The Handbook of Brain Theory and Neural Networks, (1st edition). MIT Press, 922-925. 1995

Link to publication [58] Download Bibtex entry [59]

Pattern Recognition [60]

Opper, M.

Computersimulations in Physics, 20. IFF- Summer School KFA Juelich, 29.1–29.12. 1989

Download Bibtex entry [61]

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