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General Bounds on the Mutual Information Between a Parameter and $n$ Conditionally Independent Observations [21]

Haussler, D. and Opper, M.

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

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

Supervised Learning: Information Theoretic Bounds on Predictive Errors [24]

Opper, M. and Haussler, D.

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

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

Learning in Artificial Neural Networks: The Statistical Mechanics Approach [27]

Opper, M.

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

Download Bibtex Eintrag [28]

Query by committee [29]

Seung, H. S., Opper, M. and Sompolinsky, H.

Proceedings of the Fifth Annual Conference on Computational Learning Theory. ACM Press, 287-294. 1992

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

Estimating Average - Case Learning Curves Using Bayesian, Statistical Physics and VC Dimension Methods [32]

Haussler, D., Kearns, M., Opper, M. and Schapire, R. E.

Advances in Neural Information Processing Systems 4. Morgan Kaufmann, 855–862. 1992

Download Bibtex Eintrag [33]

Calculation of the Learning Curve of Bayes Optimal Classification Algorithm for Learning a Perceptron With Noise [34]

Opper, M. and Haussler, D.

Proceedings of the Fourth Annual Conference on Computational Learning Theory. Morgan Kaufmann, 75–87. 1991

Download Bibtex Eintrag [35]

Statistical Mechanics of Learning in Neural Network Models [36]

Opper, M., Diederich, S. and Anlauf, J. K.

Neural Networks from Models to Applications. I.D.S.E.T., Paris, 235–243. 1988

Download Bibtex Eintrag [37]

Learning by Error Correction in Spin Glass Models of Neural Networks [38]

Diederich, S., Opper, M., Henkel, R. D. and Kinzel, W.

Computer Simulations in Brain Science. Cambridge University Press. 1988

Download Bibtex Eintrag [39]

Resonant and Quasiclassical Excitations of Solitons in the Alpha- Helix [40]

Bolterauer, H., Henkel, R. D. and Opper, M.

Structure, Coherence and Chaos in Dynamical Systems. Manchester University Press, 625–631. 1986

Download Bibtex Eintrag [41]

Statistische Mechanik des Lernens in neuronalen Netzwerken (Statistical mechanics of learning in neural networks [42]

Opper, M.

1991

Download Bibtex Eintrag [43]

Reinforcement learning with Gaussian Processes [44]

Seiler, J.

2012

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

Calculating eddy currents for turbomolecular pumps in magnetic fields [47]

Diederich, S. and Opper, M.

1985

Download Bibtex Eintrag [48]

Probabilistic and Genetic Attacks on the Key-Exchange Protocol Using Permutation Parity Machines [49]

Seoane, L. F.

2011

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

Nichtlineare Anregungen als Quasiteilchen in der Toda–Kette (Nonlinear excitations as quasiparticles in the Toda chain) [52]

Opper, M.

1983

Download Bibtex Eintrag [53]

A Tractable Approximation to Optimal Point Process Filtering: Application to Neural Encoding [54]

Harel, Y., Meir, R. and Opper, M.

Advances in Neural Information Processing Systems 28, 1594–1602. 2015

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

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