Matthias W. Seeger
Affiliations:- Amazon Development Center Germany, Berlin
- École Polytechnique Fédérale de Lausanne, School of Computer and Communication Sciences
- Max Planck Institute for Informatics, Saarbrücken
According to our database1,
Matthias W. Seeger
authored at least 72 papers
between 1999 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
On csauthors.net:
Bibliography
2024
2023
Explaining Multiclass Classifiers with Categorical Values: A Case Study in Radiography.
Proceedings of the Trustworthy Machine Learning for Healthcare, 2023
Proceedings of the International Conference on Machine Learning, 2023
2022
Syne Tune: A Library for Large Scale Hyperparameter Tuning and Reproducible Research.
Proceedings of the International Conference on Automated Machine Learning, 2022
Proceedings of the International Conference on Automated Machine Learning, 2022
2021
CoRR, 2021
Overfitting in Bayesian Optimization: an empirical study and early-stopping solution.
CoRR, 2021
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
2020
Proceedings of the 37th International Conference on Machine Learning, 2020
2019
Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning.
CoRR, 2019
2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
2017
Approximate Bayesian Inference in Linear State Space Models for Intermittent Demand Forecasting at Scale.
CoRR, 2017
Proceedings of the 34th International Conference on Machine Learning, 2017
2016
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
2015
Proceedings of The 7th Asian Conference on Machine Learning, 2015
2014
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014
Proceedings of the IEEE International Conference on Services Computing, SCC 2014, Anchorage, AK, USA, June 27, 2014
2013
Proceedings of the 30th International Conference on Machine Learning, 2013
2012
Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting.
IEEE Trans. Inf. Theory, 2012
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012
Proceedings of the 29th International Conference on Machine Learning, 2012
2011
SIAM J. Imaging Sci., 2011
Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011
2010
Proceedings of the From Motor Learning to Interaction Learning in Robots, 2010
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010
2009
Speeding up Magnetic Resonance Image Acquisition by Bayesian Multi-Slice Adaptive Compressed Sensing.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009
Proceedings of the 26th Annual International Conference on Machine Learning, 2009
Proceedings of the 26th Annual International Conference on Machine Learning, 2009
Large Scale Variational Inference and Experimental Design for Sparse Generalized Linear Models.
Proceedings of the Sampling-based Optimization in the Presence of Uncertainty, 26.04., 2009
Proceedings of the Sampling-based Optimization in the Presence of Uncertainty, 26.04., 2009
2008
IEEE Trans. Inf. Theory, 2008
Cross-Validation Optimization for Large Scale Structured Classification Kernel Methods.
J. Mach. Learn. Res., 2008
J. Mach. Learn. Res., 2008
Proceedings of the Advances in Neural Information Processing Systems 21, 2008
Proceedings of the Advances in Neural Information Processing Systems 21, 2008
Proceedings of the Machine Learning, 2008
Proceedings of the 16th European Symposium on Artificial Neural Networks, 2008
Proceedings of the American Control Conference, 2008
2007
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007
Experimental design for efficient identification of gene regulatory networks using sparse Bayesian models.
BMC Syst. Biol., 2007
Proceedings of the Advances in Neural Information Processing Systems 20, 2007
Proceedings of the Machine Learning: ECML 2007, 2007
2006
Cross-Validation Optimization for Large Scale Hierarchical Classification Kernel Methods.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006
Proceedings of the Semi-Supervised Learning, 2006
2005
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005
2004
2003
Bayesian Gaussian process models : PAC-Bayesian generalisation error bounds and sparse approximations.
PhD thesis, 2003
Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, 2003
2002
J. Mach. Learn. Res., 2002
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002
2001
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001
An Improved Predictive Accuracy Bound for Averaging Classifiers.
Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001
2000
Proceedings of the Advances in Neural Information Processing Systems 13, 2000
The Effect of the Input Density Distribution on Kernel-based Classifiers.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000
1999
Bayesian Model Selection for Support Vector Machines, Gaussian Processes and Other Kernel Classifiers.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999