| 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/ |
| search externally: | Google Schoolar, CiteSeer, Live Search Academic, DBlife, Scirus |
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:
|
Information consistency of nonparametric Gaussian process methods
as author at Workshops, 15 views |
||||
|
Compressed Sensing and Bayesian Experimental Design
as author at The 25th International Conference on Machine Learning (ICML 2008), together with: Hannes Nickisch, 160 views |
||||
|
Introduction to the Workshop
as author at NIPS '07 Workshop on Approximate Bayesian Inference in Continuous/Hybrid Models, 45 views |
||||

