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Book Chapter (1)

1.
Book Chapter
Gehler, P.; Schölkopf, B.: An introduction to kernel learning algorithms. In: Kernel Methods for Remote Sensing Data Analysis, pp. 25 - 48 (Eds. Camps-Valls, G.; Bruzzone, L.). Wiley, New York, NY, USA (2009)

Conference Paper (10)

2.
Conference Paper
Gehler, P.; Rother, C.; Kiefel, M.; Zhang, L.; Schölkopf, B.: Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance. In: Advances in Neural Information Processing Systems 24, pp. 765 - 773 (Eds. Shawe-Taylor, J.; Zemel, R.; Bartlett, P.; Pereira, F.; Weinberger, K.). Twenty-Fifth Annual Conference on Neural Information Processing Systems (NIPS 2011), Granada, Spain. Curran, Red Hook, NY, USA (2012)
3.
Conference Paper
Dinuzzo, F.; Ong, C.; Gehler, P.; Pillonetto, G.: Learning output kernels with block coordinate descent. In: 28th International Conference on Machine Learning (ICML 2011), pp. 49 - 56 (Eds. Getoor, L.; Scheffer, T.). 28th International Conference on Machine Learning (ICML 2011), Bellevue, WA, USA. International Machine Learning Society, Madison, WI, USA (2011)
4.
Conference Paper
Gehler, P.; Nowozin, S.: On Feature Combination for Multiclass Object Classification. In: 2009 IEEE 12th International Conference on Computer Vision, pp. 221 - 228. Twelfth IEEE International Conference on Computer Vision, Kyoto, Japan, September 29, 2009 - October 02, 2009. IEEE Computer Society, Piscataway, NJ, USA (2009)
5.
Conference Paper
Gehler, P.; Nowozin, S.: Let the Kernel Figure it Out: Principled Learning of Pre-processing for Kernel Classifiers. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp. 2836 - 2843. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Miami Beach, FL, USA, June 20, 2009 - June 25, 2009. IEEE Service Center, Piscataway, NJ, USA (2009)
6.
Conference Paper
Gehler, P.; Nowozin, S.: Infinite Kernel Learning. In: NIPS 2008 Workshop: Kernel Learning: Automatic Selection of Optimal Kernels (LK ASOK 2008), pp. 1 - 4. NIPS 2008 Workshop: Kernel Learning: Automatic Selection of Optimal Kernels (LK ASOK 2008), Whistler, BC, Canada, December 13, 2008. (2008)
7.
Conference Paper
Gehler, P.; Rother, C.; Blake, A.; Minka, T.; Sharp, T.: Bayesian Color Constancy Revisited. In: 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1 - 8. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), Anchorage, AK, USA, June 23, 2008 - June 28, 2008. IEEE, Piscataway, NJ, USA (2008)
8.
Conference Paper
Gehler, P.; Chapelle, O.: Deterministic Annealing for Multiple-Instance Learning. In: Artificial Intelligence and Statistics, 21-24 March 2007, San Juan, Puerto Rico, pp. 123 - 130 (Eds. Meila, M.; Shen, X.). 11th International Conference on Artificial Intelligence and Statistics (AISTATS 2007), San Juan, Puerto Rico, March 21, 2007 - March 24, 2007. International Machine Learning Society, Madison, WI, USA (2007)
9.
Conference Paper
Franz, M.; Gehler, P.: How to choose the covariance for Gaussian process regression independently of the basis. In: Workshop Gaussian Processes in Practice (GPIP 2006), pp. 1 - 4. Workshop Gaussian Processes in Practice (GPIP 2006), Bletchley Park, UK, June 12, 2006 - June 13, 2006. videolectures.net, Scottsdale, AZ, USA (2006)
10.
Conference Paper
Gehler, P.; Holub, A.; Welling, M.: The Rate Adapting Poisson Model for Information Retrieval and Object Recognition. In: ICML '06: Proceedings of the 23rd International Conference on Machine Learning, pp. 337 - 344 (Eds. Cohen, W.; Moore, A.). 23rd International Conference on Machine Learning (ICML 2006), Pittsburgh, PA, USA, June 25, 2006 - June 29, 2006. ACM Press, New York, NY, USA (2006)
11.
Conference Paper
Gehler, P.; Welling, M.: Products of "Edge-perts". In: Advances in Neural Information Processing Systems 18: Proceedings of the 2005 Conference, pp. 419 - 426 (Eds. Weiss, Y.; Schölkopf, B.; Platt, J.). Nineteenth Annual Conference on Neural Information Processing Systems (NIPS 2005), Vancouver, BC, Canada, December 05, 2005 - December 08, 2005. MIT Press, Cambridge, MA, USA (2006)

Thesis - PhD (1)

12.
Thesis - PhD
Gehler, P.: Kernel Learning Approaches for Image Classification. Dissertation, 159 pp., Universität des Saarlandes, Saarbrücken, Germany (2009)

Report (2)

13.
Report
Gehler, P.; Nowozin, S.: Infinite Kernel Learning (Technical Report of the Max Planck Institute for Biological Cybernetics, 178). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2008), 12 pp.
14.
Report
Gehler, P.; Franz, M.: Implicit Wiener Series: Part II: Regularised estimation (Technical Report of the Max Planck Institute for Biological Cybernetics, 148). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2006), 11 pp.
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