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author = Seeger, Matthias (13 entries)  Select: All None   Action: Show BibTeX

Matthias Seeger. 2006. An Overview on Semi-Supervised Learning Methods. [Semisupervised] ppt google scholar
Matthias Seeger. 2006. Bayesian Modelling for Data Analysis and Learning from Data. Notes and slides on the course held at IK 2006. [Bayes, npbayes] pdf google scholar
Matthias Seeger. 2005. Bayesian Gaussian Process Models: PAC-Bayesian Generalisation Error Bounds and Sparse Approximations. University of Edinburgh. [Bayes, Nonparametric, npbayes] pdf google scholar
Matthias Seeger. 2005. Gaussian Processes for Machine Learning: Where Are We and Where Could We Go?. [Bayes, Nonparametric, npbayes] pdf google scholar
Matthias Seeger. 2004. Gaussian Processes for Machine Learning. [Bayes, Nonparametric, npbayes] pdf google scholar
Matthias Seeger. 2002. Bayesian Gaussian Processes. [Bayes, Nonparametric, npbayes] pdf google scholar
Matthias Seeger. 2002. Learning with labeled and unlabeled data. [Semisupervised] pdf google scholar
Matthias Seeger. 2002. Relationships between Gaussian processes, Support Vector machines and Smoothing Splines. [Bayes, Nonparametric, SVM, npbayes] pdf google scholar
Matthias Seeger. 2001. Learning with labeled and unlabeled data. [Semisupervised] ps google scholar
Matthias Seeger. 1999. Bayesian methods for Support Vector machines and Gaussian processes. [Bayes, Nonparametric, SVM, npbayes] pdf google scholar
Matthias Seeger. 1998. Bayesian Methods for Gaussian Processes, November. Seminar of Statistische Lerntheorie, Karlsruhe, Germany. [Bayes, Nonparametric, npbayes] ps google scholar
Matthias Seeger, et al. Efficient Nonparametric Bayesian Modelling with Sparse Gaussian Process Approximations. [Bayes, Nonparametric, npbayes] pdf google scholar
Matthias Seeger. The Proof of McAllester's PAC-Bayesian Theorem. [ML] pdf google scholar

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