Mathias Seeger
email:seeger (at) tuebingen (dot) mpg (dot) de
organization:Max Planck Institute for Biological Cybernetics
phone:++49-7071-601583
homepage:http://www.kyb.tuebingen.mpg.de/bs/people/seeger/
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Description

I did my PhD in Informatics at Edinburgh University (UK) with Chris Williams. I am a fan of guess-what comix. I moved on to sunny California to do a postdoc at UC Berkeley with Michael Jordan and Peter Bartlett. Currently, I work in Bernhard Schoelkopf's group at the Max Planck Institute for Biological Cybernetics in Tuebingen, Germany.

I am interested in Gaussian process models and other non-parametric methods, PAC-Bayesian bounding techniques, support vector machines, Bayesian learning, adaptive metrics, variational approximations to Bayesian inference, supervised learning with partially unlabeled data, and convex optimization. Recently I got interested in temporal and spatiotemporal models for neuronal data, in and Bayesian experimental design (with applications to Bayesian gene regulatory network identification, undersampled fMRI reconstruction, and compressed sensing).


Lectures:
Mathias Seeger Information consistency of nonparametric Gaussian process methods

as author at Workshops,
15 views

Mathias Seeger Compressed Sensing and Bayesian Experimental Design

as author at The 25th International Conference on Machine Learning (ICML 2008),
together with: Hannes Nickisch,
160 views

Mathias Seeger Introduction to the Workshop

as author at NIPS '07 Workshop on Approximate Bayesian Inference in Continuous/Hybrid Models,
45 views