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||'''Erster Termin für Themenvergabe'''|| Mittwoch, 16.11.2011, 10:00-12:00 Uhr, Raum FR 6046 || | ||'''Erster Termin für Themenvergabe'''|| Mittwoch, 16.11.2011, 10:15-10:45 Uhr, Raum FR 6046 || |
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=== Topics (tentative) === || '''Paper(s)''' || '''Betreuer''' || '''Vortragender''' || || Nonlinear Dimensionality Reduction by Locally Linear Embedding [[http://www.sciencemag.org/content/vol290/issue5500/|link]] <<BR>> Roweis, S. T. and Saul, L. K., 2000 || || || || Gaussian Processes - A Replacement for Supervised Neural Networks? [[ftp://wol.ra.phy.cam.ac.uk/pub/mackay/gp.ps.gz|link]] <<BR>> MacKay, D. J. C., 1997 || || || || Factor Graphs and the Sum-Product Algorithm [[http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.54.1570&rep=rep1&type=pdf|link]] <<BR>> Kschischang, , Frey, and Loeliger, , 2001 || || || || Gaussian Processes in Machine Learning [[http://dx.doi.org/10.1007/978-3-540-28650-9_4|link]] <<BR>> Rasmussen, C. E., 2003 || || || || A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition [[http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.131.2084&rep=rep1&type=pdf|link]] <<BR>> Rabiner, L. R., 1989 || || || || Decoding by Linear Programming [[http://arxiv.org/pdf/math/0502327|link]] <<BR>> Candes, and Tao, , 2005 || || || || Self-organizing formation of topologically correct feature maps <<BR>> Kohonen, T., 1982 || || || || Special Invited Paper. Additive Logistic Regression: A Statistical View of Boosting [[http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.126.7436&rep=rep1&type=pdf|link]] <<BR>> Friedman, J., Hastie, T. and Tibshirani, R., 2000 || || || || Expectation Propagation for approximate Bayesian inference [[http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.86.1319&rep=rep1&type=pdf|link]] <<BR>> Minka, T. P., 2001 || || || || A new look at the statistical model identification [[http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=1100705|link]] <<BR>> Akaike, H., 1974 || || || || Error Correction via Linear Programming [[http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.91.2255&rep=rep1&type=pdf|link]] <<BR>> Candes, , Rudelson, , Tao, and Vershynin, , 2005 || || || || A Global Geometric Framework for Nonlinear Dimensionality Reduction [[http://isomap.stanford.edu/|link]] <<BR>> Tenenbaum, J. B., de Silva, V. and Langford, J. C., 2000 || || || || An Introduction to MCMC for Machine Learning [[http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.13.7133&rep=rep1&type=pdf|link]] <<BR>> Andrieu, , de Freitas, , Doucet, and Jordan, , 2003 || || || || Perspectives on Sparse Bayesian Learning [[http://books.nips.cc/papers/files/nips16/NIPS2003_AA32.pdf|link]] <<BR>> Wipf, D. P., Palmer, J. A. and Rao, B. D., 2003 || || || || Induction of decision trees [[http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.167.3624&rep=rep1&type=pdf|link]] <<BR>> Quinlan, R., 1986 || || || || A Fast Learning Algorithm for Deep Belief Nets [[http://neco.mitpress.org/cgi/content/abstract/18/7/1527|link]] <<BR>> Hinton, G. E., Osindero, S. and Teh, Y. W., 2006 || || || || How to Use Expert Advice [[http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.86.7476&rep=rep1&type=pdf|link]] <<BR>> Cesa-Bianchi, , Freund, , Haussler, , Helmbold, , Schapire, and Warmuth, , 1997 || || || || A View of the EM Algorithm that Justifies Incremental, Sparse, and other Variants [[http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.33.2557|link]] <<BR>> Neal, R. and Hinton, G., 1998 || || || || Probabilistic Inference using Markov Chain Monte Carlo Methods [[http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.36.9055&rep=rep1&type=pdf|link]] <<BR>> Neal, R. M., 1993 || || || || Model Selection Using the Minimum Description Length Principle [[http://www.amstat.org/publications/tas/Bryant.htm|link]] <<BR>> Bryant, P. G. and Cordero-Brana, O. I., 2000 || || || || Hierarchical Mixtures of Experts and the EM Algorithm [[http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.52.7391&rep=rep1&type=pdf|link]] <<BR>> Jordan, M. I. and Jacobs, R. A., 1994 || || || || Gaussian Processes in Reinforcement Learning [[http://books.nips.cc/papers/files/nips16/NIPS2003_CN01.pdf|link]] <<BR>> Rasmussen, C. E. and Kuss, M., 2003 || || || || An introduction to variational methods for graphical models [[http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.61.4999&rep=rep1&type=pdf|link]] <<BR>> Jordan, M. I., Ghahramani, Z. and Jaakkola, T. S., 1999 || || || |
Block-Seminar "Classical Topics in Machine Learning"
Termine und Informationen
Erster Termin für Themenvergabe |
Mittwoch, 16.11.2011, 10:15-10:45 Uhr, Raum FR 6046 |
Verantwortlich |
|
Ansprechtpartner(in) |
|
Sprechzeiten |
Nach Vereinbarung |
Sprache |
Englisch |
Anrechenbarkeit |
Wahlpflicht LV im Modul Maschinelles Lernen I (Informatik M.Sc.) |