Articles (7): |
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Seeger M  and Nickisch H (2011) Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models
SIAM Journal on Imaging Sciences 4(1) 166-199.
 
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Seeger M , Nickisch H , Pohmann R and Schölkopf B (2010) Optimization of k-Space Trajectories for Compressed Sensing by Bayesian Experimental Design
Magnetic Resonance in Medicine 63(1) 116-126.
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Nguyen-Tuong D , Seeger M and Peters J (2009) Model Learning with Local Gaussian Process Regression
Advanced Robotics 23(15) 2015-2034.
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Seeger M (2008) Cross-validation Optimization for Large Scale Structured Classification Kernel Methods
Journal of Machine Learning Research 9 1147-1178.
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Seeger MW , Kakade SM and Foster DP (2008) Information Consistency of Nonparametric Gaussian Process Methods
IEEE Transactions on Information Theory 54(5) 2376-2382.
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Seeger MW (2008) Bayesian Inference and Optimal Design for the Sparse Linear Model
Journal of Machine Learning Research 9 759-813.
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Steinke F , Seeger M and Tsuda K (2007) Experimental design for efficient identification of gene regulatory networks using sparse Bayesian models
BMC Systems Biology 1(51) 1-15.
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Conference papers (13): |
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Seeger M and Nickisch H (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, 14th International Conference on Artificial Intelligence and Statistics, MIT Press, Cambridge, MA, USA, 652-660.
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Seeger MW , Nickisch H , Pohmann R and Schölkopf B (2009) Bayesian Experimental Design of Magnetic Resonance Imaging Sequences
In: Advances in neural information processing systems 21, (Ed) D Koller, D Schuurmans, Y Bengio and L Bottou, 22nd Annual Conference on Neural Information Processing Systems (NIPS 2008), Curran, Red Hook, NY, USA, 1441-1448.
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Nickisch H and Seeger MW (2009) Convex variational Bayesian inference for large scale generalized linear models
In: ICML 2009, (Ed) Danyluk, A. , L. Bottou, M. Littman, 26th International Conference on Machine Learning, ACM Press, New York, NY, USA, 761-768.
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Nguyen-Tuong D , Seeger M and Peters J (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, Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS 2008), Curran, Red Hook, NY, USA, 1193-1200.
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Gerwinn S , Macke J , Seeger M and Bethge M (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, Twenty-First Annual Conference on Neural Information Processing Systems (NIPS 2007), Curran, Red Hook, NY, USA, 529-536.
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Seeger MW and Nickisch H (2008) Compressed Sensing and Bayesian Experimental Design
In: ICML 2008, (Ed) Cohen, W. W., A. McCallum, S. Roweis, 25th International Conference on Machine Learning, ACM Press, New York, NY, USA, 912-919.
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Nguyen-Tuong D , Seeger M and Peters J (2008) Computed Torque Control with Nonparametric Regression Models
In: ACC 2008, 2008 American Control Conference, IEEE Service Center, Piscataway, NJ, USA, 212-217.
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Nguyen-Tuong D , Peters J , Seeger M and Schölkopf B (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, 16th European Symposium on Artificial Neural Networks (ESANN 2008), d-side, Evere, Belgium, 13-18.
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Seeger M , Gerwinn S and Bethge M (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, 18th European Conference on Machine Learning, Springer, Berlin, Germany, 298-309.
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Seeger M (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, Twentieth Annual Conference on Neural Information Processing Systems (NIPS 2006), MIT Press, Cambridge, MA, USA, 1233-1240.
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Seeger M , Steinke F and Tsuda K (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, 11th International Conference on Artificial Intelligence and Statistics, JMLR, Cambridge, MA, USA, 444-451.
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Shen Y , 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, Nineteenth Annual Conference on Neural Information Processing Systems (NIPS 2005), MIT Press, Cambridge, MA, USA, 1225-1232.
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Kakade S , 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, Nineteenth Annual Conference on Neural Information Processing Systems (NIPS 2005), MIT Press, Cambridge, MA, USA, 619-626.
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Contributions to books (1): |
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Nguyen-Tuong D , Seeger M and Peters J : Real-Time Local GP Model Learning, 193-207.
In: From Motor Learning to Interaction Learning in Robots, (Ed) Sigaud, O. , J. Peters, Springer, Berlin, Germany, (2010).
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Technical reports (4): |
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Seeger M and Nickisch H : Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference, Max Planck Institute for Biological Cybernetics, (2010).
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Seeger M and Nickisch H : Large Scale Variational Inference and Experimental Design for Sparse Generalized Linear Models, Max Planck Institute for Biological Cybernetics, (2010).
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Seeger MW and Nickisch H : Large Scale Variational Inference and Experimental Design for Sparse Generalized Linear Models, 175, Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, (2008).
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Seeger M and Chapelle O : Cross-Validation Optimization for Structured Hessian Kernel Methods, Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, (2006).
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Posters (3): |
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Blecher W , Pohmann R , Schölkopf B and Seeger M (2011): Model based reconstruction for GRE EPI, 28th Annual Scientific Meeting ESMRMB 2011, Leipzig, Germany, Magnetic Resonance Materials in Physics, Biology and Medicine, 24(Supplement 1) 493-494.
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Seeger M , Nickisch H , Pohmann R and Schölkopf B (2009): Optimization of k-Space Trajectories by Bayesian Experimental Design, 17th Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM 2009), Honolulu, HI, USA.
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Gerwinn S , Seeger M , Zeck G and Bethge M (2007): Bayesian Neural System identification: error bars, receptive fields and neural couplings, 31st Göttingen Neurobiology Conference, 31 360.
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