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Publikationsliste

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Z-Lernen auf diskreten Markov-Entscheidungs-Problemen mit zustandsabhängigen Aktionen [20]

Bossert, T.

2013 TU Berlin

Link zur Publikation [21] Download Bibtex Eintrag [22]

Efficient stochastic control with Kullback Leibler costs using kernel methods [23]

Sokoloski, S.

2013 TU Berlin

Link zur Publikation [24] Download Bibtex Eintrag [25]

Meta Learning in Recommendation Systems [26]

Seiler, J.

2013 TU Berlin

Link zur Publikation [27] Download Bibtex Eintrag [28]

Efficient Optimal Control for Multi-Agent Jump Processes [29]

Schlegel, A.

2013 TU Berlin

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

Das variationale Dirichlet Prozess Mixture Modell [32]

Batz, P.

2010 HU Berlin

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

Improving on Expectation Propagation [35]

Opper, M., Paquet, U. and Winther, O.

Advances in Neural Information Processing Systems 21. MIT Press. 2009

Download Bibtex Eintrag [36]

Approximate inference for stochastic reaction processes [37]

Ruttor, A., Sanguinetti, G. and Opper, M.

Learning and Inference in Computational Systems Biology. The MIT Press, 189–205. 2009

Link zur Publikation [38] Download Bibtex Eintrag [39]

Variational Markov Chain Monte Carlo for Inference in Partially Observed Nonlinear Diffusions [40]

Shen, Y., Archambeau, C., Cornford, D. and Opper, M.

Proceedings of the Workshop Inference and Estimation in Probabilistic Time-Series Models, 67-78. 2008

Download Bibtex Eintrag [41]

Variational Inference for Diffusion Processes [42]

Archambeau, C., Opper, M., Shen, Y., Cornford, D. and Shawe-Taylor, J.

Advances in Neural Information Processing Systems 20. MIT Press, 17–24. 2008

Download Bibtex Eintrag [43]

Variational inference for Markov jump processes [44]

Opper, M. and Sanguinetti, G.

Advances in Neural Information Processing Systems 20. MIT Press, 1105–1112. 2008

Download Bibtex Eintrag [45]

An Approximate Inference Approach for the PCA Reconstruction Error [46]

Opper, M.

Advances in Neural Information Processing Systems 18. MIT Press. 2006

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

Approximate Inference in Probabilistic Models [49]

Opper, M. and Winther, O.

Algorithmic Learning Theory. Springer Verlag, 494–504.. 2004

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

The Complexity of Learning with Supportvector Machines - A Statistical Physics Study [52]

Opper, M.

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

Link zur Publikation [53] Download Bibtex Eintrag [54]

Statistical Mechanics of Generalization [55]

Opper, M.

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

Link zur Publikation [56] Download Bibtex Eintrag [57]

Advanced Mean Field Methods: Theory and Practice [58]

||MIT Press. 2001

Download Bibtex Eintrag [59]

vor >> [75]
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