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» Kernels for Global Constraints
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CVPR
2011
IEEE
12 years 11 months ago
Kernelized Structural SVM Learning for Supervised Object Segmentation
Object segmentation needs to be driven by top-down knowledge to produce semantically meaningful results. In this paper, we propose a supervised segmentation approach that tightly ...
Luca Bertelli, Tianli Yu, Diem Vu, Salih Gokturk
AMAI
2004
Springer
14 years 1 months ago
Combining Symmetry Breaking with Other Constraints: Lexicographic Ordering with Sums
Abstract. We introduce a new global constraint which combines together the lexicographic ordering constraint with two sum constraints. Lexicographic ordering constraints are freque...
Brahim Hnich, Zeynep Kiziltan, Toby Walsh
CORR
2011
Springer
207views Education» more  CORR 2011»
13 years 2 months ago
The AllDifferent Constraint with Precedences
We propose ALLDIFFPREC, a new global constraint that combines together an ALLDIFFERENT constraint with precedence constraints that strictly order given pairs of variables. We ident...
Christian Bessiere, Nina Narodytska, Claude-Guy Qu...
ICML
2008
IEEE
14 years 8 months ago
Graph kernels between point clouds
Point clouds are sets of points in two or three dimensions. Most kernel methods for learning on sets of points have not yet dealt with the specific geometrical invariances and pra...
Francis R. Bach
CVPR
2005
IEEE
14 years 9 months ago
Mercer Kernels for Object Recognition with Local Features
A new class of kernels for object recognition based on local image feature representations are introduced in this paper. These kernels satisfy the Mercer condition and incorporate...
Siwei Lyu