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Nobody
Matthias Seeger
Dr.
Position: Research Scientist
Room no.: 208

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2011
Articles
Conference Papers
  • M. Seeger, H. Nickisch (2011). Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference In: JMLR Workshop and Conference Proceedings Volume 15: AISTATS 2011, (Ed) Gordon, G. , D. Dunson, M. Dudík , MIT Press, Cambridge, MA, USA, 652-660, 14th International Conference on Artificial Intelligence and Statistics
Technical Reports
Posters
2010
Articles
Contributions to books
Technical Reports
  • M. Seeger, H. Nickisch (2010). Large Scale Variational Inference and Experimental Design for Sparse Generalized Linear Models Max Planck Institute for Biological Cybernetics
2009
Articles
Conference Papers
  • H. Nickisch, MW. Seeger (2009). Convex variational Bayesian inference for large scale generalized linear models In: ICML 2009, (Ed) Danyluk, A. , L. Bottou, M. Littman, Proceedings of the 26th International Conference on Machine Learning (ICML 2009), ACM Press, New York, NY, USA, 761-768, 26th International Conference on Machine Learning
  • D. Nguyen-Tuong, M. Seeger, J. Peters (2009). Local Gaussian Process Regression for Real Time Online Model Learning and Control In: Advances in neural information processing systems 21, (Ed) Koller, D. , D. Schuurmans, Y. Bengio, L. Bottou, Advances in neural information processing systems 21 : 22nd Annual Conference on Neural Information Processing Systems 2008, Curran, Red Hook, NY, USA, 1193-1200, ISBN: 978-1-605-60949-2, Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS 2008)
  • MW. Seeger, H. Nickisch, R. Pohmann, B. Schölkopf (2009). Bayesian Experimental Design of Magnetic Resonance Imaging Sequences In: Advances in neural information processing systems 21, (Ed) D Koller and D Schuurmans and Y Bengio and L Bottou, Advances in neural information processing systems 21 : 22nd Annual Conference on Neural Information Processing Systems 2008, Curran, Red Hook, NY, USA, 1441-1448, ISBN: 978-1-605-60949-2, 22nd Annual Conference on Neural Information Processing Systems (NIPS 2008)
Posters
2008
Articles
  • M. Seeger (2008). Cross-validation Optimization for Large Scale Structured Classification Kernel Methods Journal of Machine Learning Research, 9, 1147-1178
  • MW. Seeger, SM. Kakade, DP. Foster (2008). Information Consistency of Nonparametric Gaussian Process Methods IEEE Transactions on Information Theory, 54, (5), 2376-2382
  • MW. Seeger (2008). Bayesian Inference and Optimal Design for the Sparse Linear Model Journal of Machine Learning Research, 9, 759-813
Technical Reports
  • MW. Seeger, H. Nickisch (2008). Large Scale Variational Inference and Experimental Design for Sparse Generalized Linear Models Max-Planck Institute for Biological Cybernetics, Tübingen, Germany
Conference Papers
  • D. Nguyen-Tuong, J. Peters, M. Seeger, B. Schölkopf (2008). Learning Inverse Dynamics: A Comparison In: Advances in Computational Intelligence and Learning: Proceedings of the European Symposium on Artificial Neural Networks, (Ed) M Verleysen, Advances in Computational Intelligence and Learning: Proceedings of the European Symposium on Artificial Neural Networks (ESANN 2008), d-side, Evere, Belgium, 13-18, 16th European Symposium on Artificial Neural Networks (ESANN 2008)
  • MW. Seeger, H. Nickisch (2008). Compressed Sensing and Bayesian Experimental Design In: ICML 2008, (Ed) Cohen, W. W., A. McCallum, S. Roweis, Proceedings of the 25th International Conference on Machine Learning (ICML 2008), ACM Press, New York, NY, USA, 912-919, 25th International Conference on Machine Learning
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  • D. Nguyen-Tuong, M. Seeger, J. Peters (2008). Computed Torque Control with Nonparametric Regression Models In: ACC 2008, Proceedings of the 2008 American Control Conference (ACC 2008), IEEE Service Center, Piscataway, NJ, USA, 212-217, 2008 American Control Conference
  • S. Gerwinn, J. Macke, M. Seeger, M. Bethge (2008). Bayesian Inference for Spiking Neuron Models with a Sparsity Prior In: Advances in neural information processing systems 20, (Ed) Platt, J. C., D. Koller, Y. Singer, S. Roweis, Advances in Neural Information Processing Systems 20: 21st Annual Conference on Neural Information Processing Systems 2007, Curran, Red Hook, NY, USA, 529-536, ISBN: 978-1-605-60352-0, Twenty-First Annual Conference on Neural Information Processing Systems (NIPS 2007)
2007
Articles
Conference Papers
  • M. Seeger (2007). Cross-Validation Optimization for Large Scale Hierarchical Classification Kernel Methods In: Advances in Neural Information Processing Systems 19, (Ed) Schölkopf, B. , J. Platt, T. Hofmann, Advances in Neural Information Processing Systems 19: Proceedings of the 2006 Conference, MIT Press, Cambridge, MA, USA, 1233-1240, ISBN: 0-262-19568-2, Twentieth Annual Conference on Neural Information Processing Systems (NIPS 2006)
  • M. Seeger, F. Steinke, K. Tsuda (2007). Bayesian Inference and Optimal Design in the Sparse Linear Model In: JMLR Workshop and Conference Proceedings Volume 2: AISTATS 2007, (Ed) Meila, M. , X. Shen, Proceedings of the 11th International Conference on Artificial Intelligence and Statistics (AISTATS 2007), JMLR, Cambridge, MA, USA, 444-451, 11th International Conference on Artificial Intelligence and Statistics
  • M. Seeger, S. Gerwinn, M. Bethge (2007). Bayesian Inference for Sparse Generalized Linear Models In: ECML 2007, (Ed) Kok, J. N., J. Koronacki, R. Lopez de Mantaras, S. Matwin, D. Mladenic, A. Skowron, Machine Learning: ECML 2007, Springer, Berlin, Germany, 298-309, 18th European Conference on Machine Learning
Posters
  • S. Gerwinn, M. Seeger, G. Zeck, M. Bethge (2007). Bayesian Neural System identification: error bars, receptive fields and neural couplings 31st Göttingen Neurobiology Conference, 31, 360
2006
Conference Papers
  • Shen, Y. and Ng, AY. and Seeger, M. (2006). Fast Gaussian Process Regression using KD-Trees In: Advances in neural information processing systems 18, (Ed) Weiss, Y. , B. Schölkopf, J. Platt, Advances in Neural Information Processing Systems 18: Proceedings of the 2005 Conference, MIT Press, Cambridge, MA, USA, 1225-1232, ISBN: 0-262-23253-7, Nineteenth Annual Conference on Neural Information Processing Systems (NIPS 2005)
  • Kakade, S. and Seeger, M. and Foster, D. (2006). Worst-Case Bounds for Gaussian Process Models In: Advances in neural information processing systems 18, (Ed) Weiss, Y. , B. Schölkopf, J. Platt, Advances in Neural Information Processing Systems 18: Proceedings of the 2005 Conference, MIT Press, Cambridge, MA, USA, 619-626, ISBN: 0-262-23253-7, Nineteenth Annual Conference on Neural Information Processing Systems (NIPS 2005)
Technical Reports