Heiler, M and Schnörr, C (2006). Controlling Sparseness in Non-negative Tensor Factorization. Computer Vision -- ECCV 2006. Springer. 3951 56-67

 Heiler, M and Schnörr, C (2006). Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming. J. Mach. Learning Res. 7 1385?1407. http://www.cvgpr.uni-mannheim.de/Publications

 Heiler, M and Schnörr, C (2005). Learning Sparse Image Codes by Convex Programming. Proc. Tenth IEEE Int. Conf. Computer Vision (ICCV'05). Beijing, China. 1667-1674

 Heiler, M and Schnörr, C (2005). Natural Image Statistics for Natural Image Segmentation. Int. J. Comp. Vision. 63 5?19

 Heiler, M and Schnörr, C (2005). Reverse-Convex Programming for Sparse Image Codes. Proc. Int. Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'05). Springer. 3757 600-616

 Heiler, M, Keuchel, J and Schnörr, C (2005). Semidefinite Clustering for Image Segmentation with A-priori Knowledge. Pattern Recognition, Proc. 27th DAGM Symposium. Springer. 3663 309?317

 Keuchel, J, Heiler, M and Schnörr, C (2004). Hierarchical Image Segmentation based on Semidefinite Programming. Pattern Recognition, Proc. 26th DAGM Symposium. Springer. 3175 120-128

 Heiler, M and Schnörr, C (2003). Natural Statistics for Natural Image Segmentation. Proc. IEEE Int. Conf. Computer Vision (ICCV 2003). Nice, France. 1259-1266

 Keuchel, J, Naumann, S, Heiler, M and Siegmund, A (2002). Automatic Land Cover Analysis for Tenerife by Supervised Classification using Remotely Sensed Data. Remote Sensing of Environment

 Heiler, M, Cremers, D and Schnörr, C (2001). Efficient Feature Subset Selection For Support Vector Machines. Dept. Math. and Comp. Science, University of Mannheim, Germany