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Matthias Seeger
Matthias Seeger
Principal Applied Scientist, Amazon, Berlin
Dirección de correo verificada de amazon.de - Página principal
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Citado por
Citado por
Año
Using the Nyström method to speed up kernel machines
C Williams, M Seeger
Advances in neural information processing systems 13, 2000
31292000
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
28232009
Gaussian processes for machine learning
M Seeger
International journal of neural systems 14 (02), 69-106, 2004
14172004
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
10412012
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
8592018
Fast sparse Gaussian process methods: The informative vector machine
N Lawrence, M Seeger, R Herbrich
Advances in neural information processing systems 15, 2002
7522002
Learning with labeled and unlabeled data
M Seeger
7412000
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
6712003
PAC-Bayesian generalisation error bounds for Gaussian process classification
M Seeger
Journal of machine learning research 3 (Oct), 233-269, 2002
4362002
Model learning with local gaussian process regression
D Nguyen-Tuong, M Seeger, J Peters
Advanced Robotics 23 (15), 2015-2034, 2009
4092009
Bayesian inference and optimal design in the sparse linear model
M Seeger, F Steinke, K Tsuda
Artificial Intelligence and Statistics, 444-451, 2007
3842007
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
3472008
Semiparametric latent factor models
YW Teh, M Seeger, MI Jordan
International Workshop on Artificial Intelligence and Statistics, 333-340, 2005
3212005
Bayesian Gaussian process models: PAC-Bayesian generalisation error bounds and sparse approximations
M Seeger
University of Edinburgh, 2003
2592003
The effect of the input density distribution on kernel-based classifiers
C Williams, M Seeger
Proceedings of the 17th international conference on machine learning, 1159-1166, 2000
2392000
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
2322020
Expectation propagation for exponential families
M Seeger
2132005
Computed torque control with nonparametric regression models
D Nguyen-Tuong, M Seeger, J Peters
2008 American Control Conference, 212-217, 2008
2032008
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
1882010
Scalable hyperparameter transfer learning
V Perrone, R Jenatton, MW Seeger, C Archambeau
Advances in neural information processing systems 31, 2018
1822018
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Artículos 1–20