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Order by: Author  Year  Journal

1997

Regression with Gaussian Processes: Average Case Performance

Opper, M.

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

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Metric Entropy and Minimax Risk in Classification

Haussler, D. and Opper, M.

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

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A mean field algorithm for Bayes learning in large feedforward neural networks

Opper, M. and Winther, O.

Advances in Neural Information Processing Systems 9. MIT Press, 225-231. 1997

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Dynamics of Training

Bös, S. and Opper, M.

Advances in Neural Information Processing Systems 9. MIT Press, 141-147. 1997

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1998

A Bayesian Approach to Online Learning

Opper, M.

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

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Statistical Mechanics of Learning in the Presence of Outliers

Dietrich, R. and Opper, M.

Journal of Physics A, 9131-9147. 1998

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1999

Worst Case Prediction over Sequences under Log Loss

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

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General Bounds on Bayes errors for regression with Gaussian processes

Opper, M. and Vivarelli, F.

Advances in Neural Information Processing Systems 11. MIT Press, 302-308. 1999

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Mean field methods for classification with Gaussian processes

Opper, M. and Winther, O.

Advances in Neural Information Processing Systems 11. MIT Press, 309-315. 1999

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Finite Dimensional Approximation of Gaussian Processes

Trecate, G. F., Williams, C. K. and Opper, M.

Advances in Neural Information Processing Systems 11. MIT Press, 218-224. 1999

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