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Techreport
M. Heiler, Cremers, D., and Schnörr, C., “Efficient Feature Subset Selection for Support Vector Machines”, Dept. Math. and Comp. Science, University of Mannheim, Germany, 21/2001, 2001.
Journal Article
M. Heiler and Schnörr, C., “Natural Image Statistics for Natural Image Segmentation”, Int. J. Comp. Vision, vol. 63, pp. 5–19, 2005.
M. Heiler and Schnörr, C., “Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming”, J. Mach. Learning Res., vol. 7, pp. 1385–1407, 2006.
J. Keuchel, Naumann, S., Heiler, M., and Siegmund, A., “Automatic Land Cover Analysis for Tenerife by Supervised Classification using Remotely Sensed Data”, Remote Sensing of Environment, 2002.
In Collection
M. Heiler, Keuchel, J., and Schnörr, C., “Semidefinite Clustering for Image Segmentation with A-priori Knowledge”, Pattern Recognition, Proc. 27th DAGM Symposium, vol. 3663. Springer, pp. 309–317, 2005.
Conference Paper
M. Heiler and Schnörr, C., “Reverse-Convex Programming for Sparse Image Codes”, in Proc. Int. Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'05), 2005, vol. 3757, pp. 600-616.
M. Heiler and Schnörr, C., “Natural Statistics for Natural Image Segmentation”, in Proc. IEEE Int. Conf. Computer Vision (ICCV 2003), Nice, France, 2003, pp. 1259-1266.
M. Heiler and Schnörr, C., “Learning Sparse Image Codes by Convex Programming”, in Proc. Tenth IEEE Int. Conf. Computer Vision (ICCV'05), Beijing, China, 2005, pp. 1667-1674.
J. Keuchel, Heiler, M., and Schnörr, C., “Hierarchical Image Segmentation based on Semidefinite Programming”, in Pattern Recognition, Proc. 26th DAGM Symposium, 2004, vol. 3175, pp. 120-128.
M. Heiler and Schnörr, C., “Controlling Sparseness in Non-negative Tensor Factorization”, in Computer Vision -- ECCV 2006, 2006, vol. 3951, pp. 56-67.PDF icon Technical Report (568.86 KB)