A bundle approach to efficient MAP-inference by Lagrangian relaxation

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2012, Pages 1688-1695

  Kappes, Jorg Hendrik ^a   Savchynskyy, Bogdan ^a   Schnorr, Christoph ^a  

^a UNIVERSITY OF HEIDELBERG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATE INFERENCE; BENCHMARK EXPERIMENTS; BUNDLE METHODS; DUAL OBJECTIVE FUNCTION; GRAPHICAL MODEL; KEY TECHNIQUES; LAGRANGIAN RELAXATION; NON-SMOOTH; NON-SMOOTHNESS; PROBLEM INSTANCES; PROJECTED SUBGRADIENT METHODS; SPECIFIC PROBLEMS; TUNING PARAMETER;

COMBINATORIAL OPTIMIZATION; CONVEX OPTIMIZATION; LAGRANGE MULTIPLIERS;

COMPUTER VISION;

EID: 84866653674     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2012.6247863     Document Type: Conference Paper

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