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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
29912000
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
25272009
Gaussian processes for machine learning
M Seeger
International journal of neural systems 14 (02), 69-106, 2004
11942004
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
9252012
Learning with labeled and unlabeled data
M Seeger
7332000
Fast sparse Gaussian process methods: The informative vector machine
N Lawrence, M Seeger, R Herbrich
Advances in neural information processing systems 15, 2002
7282002
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
6942018
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
6492003
PAC-Bayesian generalisation error bounds for Gaussian process classification
M Seeger
Journal of machine learning research 3 (Oct), 233-269, 2002
4182002
Model learning with local gaussian process regression
D Nguyen-Tuong, M Seeger, J Peters
Advanced Robotics 23 (15), 2015-2034, 2009
3902009
Bayesian inference and optimal design in the sparse linear model
M Seeger, F Steinke, K Tsuda
Artificial Intelligence and Statistics, 444-451, 2007
3802007
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
3182008
Semiparametric latent factor models
YW Teh, M Seeger, MI Jordan
International Workshop on Artificial Intelligence and Statistics, 333-340, 2005
3142005
Bayesian Gaussian process models: PAC-Bayesian generalisation error bounds and sparse approximations
M Seeger
University of Edinburgh, 2003
2472003
The effect of the input density distribution on kernel-based classifiers
C Williams, M Seeger
ICML'00 Proceedings of the Seventeenth International Conference on Machine …, 2000
2332000
Expectation propagation for exponential families
M Seeger
2082005
Computed torque control with nonparametric regression models
D Nguyen-Tuong, M Seeger, J Peters
2008 American Control Conference, 212-217, 2008
1962008
Leep: A new measure to evaluate transferability of learned representations
C Nguyen, T Hassner, M Seeger, C Archambeau
International Conference on Machine Learning, 7294-7305, 2020
1842020
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
1802010
Bayesian model selection for support vector machines, Gaussian processes and other kernel classifiers
M Seeger
Advances in neural information processing systems 12, 1999
1801999
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