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B. Savchynskyy, Kappes, J. H., Schmidt, S., and Schnörr, C., A Study of Nesterov's Scheme for Lagrangian Decomposition and MAP Labeling, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), accepted as oral presentation, pp. 1817 - 1823, 2011.
B. Savchynskyy, Kappes, J. H., Swoboda, P., and Schnörr, C., Global MAP-Optimality by Shrinking the Combinatorial Search Area with Convex Relaxation, in NIPS. Proceedings, 2013, pp. 1950-1958.
B. Savchynskyy and Schmidt, S., Getting Feasible Variable Estimates From Infeasible Ones: MRF Local Polytope Study, in Workshop on Inference for Probabilistic Graphical Models at ICCV. Proceedings, 2013.
B. Savchynskyy and Schmidt, S., Getting Feasible Variable Estimates From Infeasible Ones: MRF Local Polytope Study, arXiv:1210.4081, 2012.
B. Savchynskyy, Schmidt, S., Kappes, J. H., and Schnörr, C., Efficient MRF Energy Minimization via Adaptive Diminishing Smoothing, UAI. Proceedings, pp. 746-755, 2012.
B. Savchynskyy, Kappes, J. H., Schmidt, S., and Schnörr, C., A Study of Nesterov's Scheme for Lagrangian Decomposition and MAP Labeling, in IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2011.PDF icon Technical Report (408.99 KB)
B. Savchynskyy, Kappes, J. H., Schmidt, S., and Schnörr, C., A Study of Nesterov's Scheme for Lagrangian Decomposition and MAP Labeling, in IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2011.