Matthias Seeger
Matthias Seeger
Principal Applied Scientist, Amazon, Berlin
Geverifieerd e-mailadres voor amazon.de - Homepage
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Using the Nyström method to speed up kernel machines
C Williams, M Seeger
Proceedings of the 14th annual conference on neural information processing …, 2001
24502001
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
15592009
Gaussian processes for machine learning
M Seeger
International journal of neural systems 14 (02), 69-106, 2004
7342004
Learning with labeled and unlabeled data
M Seeger
7082000
Fast sparse Gaussian process methods: The informative vector machine
N Lawrence, M Seeger, R Herbrich
Proceedings of the 16th annual conference on neural information processing …, 2003
6532003
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
5202003
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
5172012
Bayesian inference and optimal design in the sparse linear model
M Seeger, F Steinke, K Tsuda
Artificial Intelligence and Statistics, 444-451, 2007
3622007
PAC-Bayesian generalisation error bounds for Gaussian process classification
M Seeger
Journal of machine learning research 3 (Oct), 233-269, 2002
3322002
Model learning with local gaussian process regression
D Nguyen-Tuong, M Seeger, J Peters
Advanced Robotics 23 (15), 2015-2034, 2009
3072009
Semiparametric latent factor models
YW Teh, M Seeger, MI Jordan
International Workshop on Artificial Intelligence and Statistics, 333-340, 2005
2752005
Local gaussian process regression for real time online model learning and control
D Nguyen-Tuong, J Peters, M Seeger
Proceedings of the 21st International Conference on Neural Information …, 2008
2472008
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
2222000
Bayesian Gaussian process models: PAC-Bayesian generalisation error bounds and sparse approximations
M Seeger
University of Edinburgh, 2003
2182003
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, 7785-7794, 2018
1962018
Expectation propagation for exponential families
M Seeger
1892005
Bayesian model selection for support vector machines, Gaussian processes and other kernel classifiers
M Seeger
Proceedings of the 13th Annual Conference on Neural Information Processing …, 2000
1662000
Computed torque control with nonparametric regression models
D Nguyen-Tuong, M Seeger, J Peters
2008 American Control Conference, 212-217, 2008
1562008
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
1452010
Fast gaussian process regression using kd-trees
Y Shen, A Ng, M Seeger
Proceedings of the 19th Annual Conference on Neural Information Processing …, 2006
1402006
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Artikelen 1–20