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Matthias Seeger
Matthias Seeger
Principal Applied Scientist, Amazon, Berlin
Verified email at amazon.de - Homepage
Title
Cited by
Cited by
Year
Using the Nyström method to speed up kernel machines
C Williams, M Seeger
Advances in neural information processing systems 13, 2000
27002000
Gaussian process optimization in the bandit setting: No regret and experimental design
N Srinivas, A Krause, SM Kakade, M Seeger
arXiv preprint arXiv:0912.3995, 2009
19732009
Gaussian processes for machine learning
M Seeger
International journal of neural systems 14 (02), 69-106, 2004
8622004
Learning with labeled and unlabeled data
M Seeger
7172000
Information-theoretic regret bounds for gaussian process optimization in the bandit setting
N Srinivas, A Krause, SM Kakade, MW Seeger
IEEE transactions on information theory 58 (5), 3250-3265, 2012
6962012
Fast sparse Gaussian process methods: The informative vector machine
N Lawrence, M Seeger, R Herbrich
Advances in neural information processing systems 15, 2002
6822002
Fast forward selection to speed up sparse Gaussian process regression
MW Seeger, CKI Williams, ND Lawrence
International Workshop on Artificial Intelligence and Statistics, 254-261, 2003
5702003
Deep state space models for time series forecasting
SS Rangapuram, MW Seeger, J Gasthaus, L Stella, Y Wang, ...
Advances in neural information processing systems 31, 2018
4002018
Bayesian inference and optimal design in the sparse linear model
M Seeger, F Steinke, K Tsuda
Artificial Intelligence and Statistics, 444-451, 2007
3692007
PAC-Bayesian generalisation error bounds for Gaussian process classification
M Seeger
Journal of machine learning research 3 (Oct), 233-269, 2002
3512002
Model learning with local gaussian process regression
D Nguyen-Tuong, M Seeger, J Peters
Advanced Robotics 23 (15), 2015-2034, 2009
3432009
Semiparametric latent factor models
YW Teh, M Seeger, MI Jordan
International Workshop on Artificial Intelligence and Statistics, 333-340, 2005
2902005
Local Gaussian process regression for real time online model learning
D Nguyen-Tuong, J Peters, M Seeger
Advances in neural information processing systems 21, 2008
2732008
Bayesian Gaussian process models: PAC-Bayesian generalisation error bounds and sparse approximations
M Seeger
University of Edinburgh, 2003
2312003
The effect of the input density distribution on kernel-based classifiers
C Williams, M Seeger
Proceedings of the 17th international conference on machine learning, 2000
2192000
Expectation propagation for exponential families
M Seeger
1992005
Computed torque control with nonparametric regression models
D Nguyen-Tuong, M Seeger, J Peters
2008 American Control Conference, 212-217, 2008
1732008
Bayesian model selection for support vector machines, Gaussian processes and other kernel classifiers
M Seeger
Advances in neural information processing systems 12, 1999
1661999
Optimization of k‐space trajectories for compressed sensing by Bayesian experimental design
M Seeger, H Nickisch, R Pohmann, B Schölkopf
Magnetic Resonance in Medicine: An Official Journal of the International …, 2010
1642010
Fast gaussian process regression using kd-trees
Y Shen, M Seeger, A Ng
Advances in neural information processing systems 18, 2005
1462005
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