direkt zum Inhalt springen

direkt zum Hauptnavigationsmenü

Sie sind hier

TU Berlin

Inhalt des Dokuments

Publikationsliste

<< zurück [1]
vor >> [17]

Learning to Generalize [21]

Opper, M.

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

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

Adaptive TAP Equations [24]

Opper, M. and Winther, O.

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

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

From Naive Mean Field Theory to the TAP Equations [27]

Opper, M. and Winther, O.

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

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

Imparare a Generalizzare (Learning to Generalize) [30]

Opper, M.

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

Download Bibtex Eintrag [31]

Statistical Mechanics of SVMs [32]

Dietrich, R., Opper, M. and Sompolinsky, H.

Advances in Large Margin Classifiers. MIT Press, 359-367. 2000

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

Gaussian Processes and SVM: Mean Field Results and Leave-One-Out [35]

Opper, M. and Winther, O.

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

Download Bibtex Eintrag [36]

Worst Case Prediction over Sequences under Log Loss [37]

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 zur Publikation [38] Download Bibtex Eintrag [39]

On the Annealed VC Entropy for Margin Classifiers: A Statistical Mechanics Study [40]

Opper, M.

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

Link zur Publikation [41] Download Bibtex Eintrag [42]

A Bayesian Approach to Online Learning [43]

Opper, M.

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

Link zur Publikation [44] Download Bibtex Eintrag [45]

Regression with Gaussian Processes: Average Case Performance [46]

Opper, M.

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

Link zur Publikation [47] Download Bibtex Eintrag [48]

Metric Entropy and Minimax Risk in Classification [49]

Haussler, D. and Opper, M.

Lecture Notes in Computer Science: Studies in Logic and Computer Science, Vol. 1261. Springer, 212-235. 1997

Link zur Publikation [50] Download Bibtex Eintrag [51]

Physics of Generalization [52]

Opper, M. and Kinzel, W.

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

Download Bibtex Eintrag [53]

Mutual Information and Bayes Methods for Learning a Distribution [54]

Haussler, D. and Opper, M.

Theory of Neural Networks, The Statistical Mechanics Perspective. World Scientific, 42–50. 1995

Link zur Publikation [55] Download Bibtex Eintrag [56]

General Bounds for Predictive Errors in Supervised Learning [57]

Opper, M. and Haussler, D.

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

Link zur Publikation [58] Download Bibtex Eintrag [59]

Perceptron Learning: The Largest Version Space [60]

Biehl, M. and Opper, M.

Theory of Neural Networks, The Statistical Mechanics Perspective. World Scientific, 59-72. 1995

Link zur Publikation [61] Download Bibtex Eintrag [62]

<< zurück [63]
vor >> [79]
------ Links: ------

Zusatzinformationen / Extras

Direktzugang

Schnellnavigation zur Seite über Nummerneingabe

Copyright TU Berlin 2008