Publications of PV Gehler
All genres
Book Chapter (1)
1.
Book Chapter
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
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
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
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
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
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
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
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
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
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
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)
Products of "Edge-perts". In: Advances in Neural Information Processing Systems 18: Proceedings of the 2005 Conference, pp. 419 - 426 (Eds. Weiss, Y.; Thesis - PhD (1)
12.
Thesis - PhD
Kernel Learning Approaches for Image Classification. Dissertation, 159 pp., Universität des Saarlandes, Saarbrücken, Germany (2009)
Report (2)
13.
Report
178). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2008), 12 pp.
Infinite Kernel Learning (Technical Report of the Max Planck Institute for Biological Cybernetics, 14.
Report
148). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2006), 11 pp.
Implicit Wiener Series: Part II: Regularised estimation (Technical Report of the Max Planck Institute for Biological Cybernetics,