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All publications by Matthias Seeger
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Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models
Mohammad E. Khan, Aleksandr Aravkin, Michael Friedlander and Matthias Seeger
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


Large Scale Variational Bayesian Inference for Structured Scale Mixture Models
Young J. Ko and Matthias Seeger
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Fast Variational Bayesian Inference for Non-Conjugate Matrix Factorization Models
Matthias Seeger and Guillaume Bouchard
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12), 2012


Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design
Niranjan Srinivas, Andreas Krause, Matthias Seeger and Sham M. Kakade
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Gaussian Covariance and Scalable Variational Inference
Matthias Seeger
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Workshop summary: Numerical mathematics in machine learning
Matthias Seeger, Suvrit Sra and John P. Cunningham
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Convex variational Bayesian inference for large scale generalized linear models
Hannes Nickisch and Matthias Seeger
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Speeding up Magnetic Resonance Image Acquisition by Bayesian Multi-Slice Adaptive Compressed Sensing
Matthias Seeger
Advances in Neural Information Processing Systems 22, 2009


Compressed sensing and Bayesian experimental design
Hannes Nickisch and Matthias Seeger
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


Bayesian Experimental Design of Magnetic Resonance Imaging Sequences
Hannes Nickisch, Rolf Pohmann, Bernhard Schölkopf and Matthias Seeger
Advances in Neural Information Processing Systems 21, 2008


Local Gaussian Process Regression for Real Time Online Model Learning
Duy Nguyen-tuong, Jan R. Peters and Matthias Seeger
Advances in Neural Information Processing Systems 21, 2008


Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
Sebastian Gerwinn, Matthias Bethge, Jakob H. Macke and Matthias Seeger
Advances in Neural Information Processing Systems 20, 2007


Bayesian Inference and Optimal Design in the Sparse Linear Model
Matthias Seeger, Florian Steinke and Koji Tsuda
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Cross-Validation Optimization for Large Scale Hierarchical Classification Kernel Methods
Matthias Seeger
Advances in Neural Information Processing Systems 19, 2006


Fast Gaussian Process Regression using KD-Trees
Yirong Shen, Matthias Seeger and Andrew Y. Ng
Advances in Neural Information Processing Systems 18, 2005


PAC-Bayesian Generalisation Error Bounds for Gaussian Process Classification
Matthias Seeger
Journal of Machine Learning Research, 2002


Fast Sparse Gaussian Process Methods: The Informative Vector Machine
Ralf Herbrich, Neil D. Lawrence and Matthias Seeger
Advances in Neural Information Processing Systems 15, 2002


Covariance Kernels from Bayesian Generative Models
Matthias Seeger
Advances in Neural Information Processing Systems 14, 2001