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List of Publications

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Order by: Author [18]  Year [19]  Journal [20]

1995

Learning of Correlated Patterns in Perceptrons [21]

López, B. J., Schröder, M. and Opper, M.

J. Phys. A, L447. 1995

Download Bibtex entry [22]

On the Relaxation of Infinite Range Spin Glasses [23]

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

J. Phys. A, 5721-5727. 1995

Link to publication [24] Download Bibtex entry [25]

Statistical Physics Estimates for the Complexity of Feedworward Neural Networks [26]

Opper, M.

Phys. Rev E, 3613–3618. 1995

Download Bibtex entry [27]

Mutual Information and Bayes Methods for Learning a Distribution [28]

Haussler, D. and Opper, M.

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

Link to publication [29] Download Bibtex entry [30]

General Bounds for Predictive Errors in Supervised Learning [31]

Opper, M. and Haussler, D.

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

Link to publication [32] Download Bibtex entry [33]

Perceptron Learning: The Largest Version Space [34]

Biehl, M. and Opper, M.

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

Link to publication [35] Download Bibtex entry [36]

Statistical Mechanics of Learning: Generalization [37]

Opper, M.

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

Link to publication [38] Download Bibtex entry [39]

General Bounds on the Mutual Information Between a Parameter and $n$ Conditionally Independent Observations [40]

Haussler, D. and Opper, M.

Proceedings of the Eighth Annual Conference on Computational Learning Theory. ACM Press, 402-411. 1995

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

Supervised Learning: Information Theoretic Bounds on Predictive Errors [43]

Opper, M. and Haussler, D.

Proceedings of the IEEE workshop on Information Theory (ITW'95), 6.2. 1995

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

Learning in Artificial Neural Networks: The Statistical Mechanics Approach [46]

Opper, M.

Supercomputing in Brain Reasearch: From Tomography to Neural Networks. World Scientific, 321–330. 1995

Download Bibtex entry [47]

Maximal Stability in Unsupervised Learning [48]

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

J. Phys. A, 2785–2797. 1995

Download Bibtex entry [49]

1996

Physics of Generalization [50]

Opper, M. and Kinzel, W.

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

Download Bibtex entry [51]

Selection of examples for the linear classifier [52]

Jung, G. and Opper, M.

J. Phys. A, 1367-1380. 1996

Link to publication [53] Download Bibtex entry [54]

Online versus Offline Learning from Random Examples: General Results [55]

Opper, M.

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

Link to publication [56] Download Bibtex entry [57]

A mean field approach to Bayes learning in feed–forward neural networks [58]

Opper, M. and Winther, O.

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

Link to publication [59] Download Bibtex entry [60]
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