graph cut

Learning Efficient Random Maximum A-Posteriori Predictors with Non-Decomposable Loss Functions NeurIPS 2013 Multi-view Object Segmentation in Space and Time ICCV 2013 Partial Enumeration and Curvature Regularization ICCV 2013 Potts Model, Parametric Maxflow and K-Submodular Functions ICCV 2013 Predicting Sufficient Annotation Strength for Interactive Foreground Segmentation ICCV 2013 Semantic Segmentation without Annotating Segments ICCV 2013 Structured Learning of Sum-of-Submodular Higher Order Energy Functions ICCV 2013 Towards Efficient and Exact MAP-Inference for Large Scale Discrete Computer Vision Problems via Combinatorial Optimization CVPR 2013 Convergence and Energy Landscape for Cheeger Cut Clustering NeurIPS 2012 Beyond Spectral Clustering - Tight Relaxations of Balanced Graph Cuts NeurIPS 2011 Improved Moves for Truncated Convex Models JMLR 2011 Information Theoretical Clustering via Semidefinite Programming AISTATS 2011 Pylon Model for Semantic Segmentation NeurIPS 2011 Spectral Clustering on a Budget AISTATS 2011 Submodular Multi-Label Learning NeurIPS 2011 Efficient Minimization of Decomposable Submodular Functions NeurIPS 2010 Semi-Supervised Learning with Max-Margin Graph Cuts AISTATS 2010 Efficient Exact Inference in Planar Ising Models NeurIPS 2008 Improved Moves for Truncated Convex Models NeurIPS 2008 On the Effectiveness of Laplacian Normalization for Graph Semi-supervised Learning JMLR 2007 Doubly Stochastic Normalization for Spectral Clustering NeurIPS 2006 On the Relation Between Low Density Separation, Spectral Clustering and Graph Cuts NeurIPS 2006