Folgen
Matthias Seeger
Matthias Seeger
Principal Applied Scientist, Amazon, Berlin
Bestätigte E-Mail-Adresse bei amazon.de - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Using the Nyström method to speed up kernel machines
C Williams, M Seeger
Advances in neural information processing systems 13, 2000
29782000
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
25162009
Gaussian processes for machine learning
M Seeger
International journal of neural systems 14 (02), 69-106, 2004
11812004
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
9202012
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
7272002
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
6872018
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
6462003
PAC-Bayesian generalisation error bounds for Gaussian process classification
M Seeger
Journal of machine learning research 3 (Oct), 233-269, 2002
4132002
Model learning with local gaussian process regression
D Nguyen-Tuong, M Seeger, J Peters
Advanced Robotics 23 (15), 2015-2034, 2009
3892009
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
3132005
Bayesian Gaussian process models: PAC-Bayesian generalisation error bounds and sparse approximations
M Seeger
University of Edinburgh, 2003
2452003
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
2072005
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
1802020
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
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20