Matthias Seeger
Matthias Seeger
Principal Applied Scientist, Amazon, Berlin
Подтвержден адрес электронной почты в домене amazon.de - Главная страница
Название
Процитировано
Процитировано
Год
Using the Nyström method to speed up kernel machines
C Williams, M Seeger
Proceedings of the 14th annual conference on neural information processing …, 2001
23322001
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
13692009
Learning with labeled and unlabeled data
M Seeger
7142000
Gaussian processes for machine learning
M Seeger
International journal of neural systems 14 (02), 69-106, 2004
6822004
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
6372003
Fast forward selection to speed up sparse Gaussian process regression
M Seeger, C Williams, N Lawrence
Artificial Intelligence and Statistics 9, 2003
4982003
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
4542012
Bayesian inference and optimal design in the sparse linear model
M Seeger, F Steinke, K Tsuda
Artificial Intelligence and Statistics, 444-451, 2007
3592007
PAC-Bayesian generalisation error bounds for Gaussian process classification
M Seeger
Journal of machine learning research 3 (Oct), 233-269, 2002
3112002
Model learning with local gaussian process regression
D Nguyen-Tuong, M Seeger, J Peters
Advanced Robotics 23 (15), 2015-2034, 2009
2832009
Semiparametric latent factor models
M Seeger, YW Teh, M Jordan
2612005
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
2322008
Bayesian Gaussian process models: PAC-Bayesian generalisation error bounds and sparse approximations
M Seeger
University of Edinburgh, 2003
2172003
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
2172000
Expectation propagation for exponential families
M Seeger
1852005
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
1672000
Computed torque control with nonparametric regression models
D Nguyen-Tuong, M Seeger, J Peters
2008 American Control Conference, 212-217, 2008
1462008
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
1412018
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
1412010
Fast gaussian process regression using kd-trees
Y Shen, A Ng, M Seeger
Proceedings of the 19th Annual Conference on Neural Information Processing …, 2006
1342006
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