Matthias Seeger
Matthias Seeger
Principal Applied Scientist, Amazon, Berlin
Verifierad e-postadress på amazon.de - Startsida
Titel
Citeras av
Citeras av
År
Using the Nyström method to speed up kernel machines
CKI Williams, M Seeger
Advances in neural information processing systems, 682-688, 2001
21392001
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
11332009
Learning with labeled and unlabeled data
M Seeger
6712000
Gaussian processes for machine learning
M Seeger
International journal of neural systems 14 (02), 69-106, 2004
6092004
Fast sparse Gaussian process methods: The informative vector machine
R Herbrich, ND Lawrence, M Seeger
Advances in neural information processing systems, 625-632, 2003
5902003
Fast forward selection to speed up sparse Gaussian process regression
M Seeger, C Williams, N Lawrence
Artificial Intelligence and Statistics 9, 2003
4452003
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
3852012
Bayesian inference and optimal design for the sparse linear model
MW Seeger
Journal of Machine Learning Research 9 (Apr), 759-813, 2008
3292008
Pac-bayesian generalisation error bounds for gaussian process classification
M Seeger
Journal of machine learning research 3 (Oct), 233-269, 2002
2832002
Model learning with local gaussian process regression
D Nguyen-Tuong, M Seeger, J Peters
Advanced Robotics 23 (15), 2015-2034, 2009
2592009
Semiparametric latent factor models
M Seeger, YW Teh, M Jordan
2332005
Local gaussian process regression for real time online model learning
D Nguyen-Tuong, JR Peters, M Seeger
Advances in neural information processing systems, 1193-1200, 2009
2092009
Bayesian Gaussian process models: PAC-Bayesian generalisation error bounds and sparse approximations
M Seeger
University of Edinburgh, 2003
2062003
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
2032000
Expectation propagation for exponential families
M Seeger
1692005
Bayesian model selection for support vector machines, Gaussian processes and other kernel classifiers
M Seeger
Advances in neural information processing systems, 603-609, 2000
1562000
Computed torque control with nonparametric regression models
D Nguyen-Tuong, M Seeger, J Peters
2008 American Control Conference, 212-217, 2008
1372008
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
1282010
Fast gaussian process regression using kd-trees
Y Shen, M Seeger, AY Ng
Advances in neural information processing systems, 1225-1232, 2006
1242006
Compressed sensing and Bayesian experimental design
MW Seeger, H Nickisch
Proceedings of the 25th international conference on Machine learning, 912-919, 2008
1182008
Systemet kan inte utföra åtgärden just nu. Försök igen senare.
Artiklar 1–20