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ISVC
2009
Springer
14 years 2 months ago
Adaptive Contextual Energy Parameterization for Automated Image Segmentation
Image segmentation techniques are predominately based on parameter-laden optimization processes. The segmentation objective function traditionally involves parameters (i.e. weights...
Josna Rao, Ghassan Hamarneh, Rafeef Abugharbieh
CVPR
2012
IEEE
11 years 10 months ago
Curvature-based regularization for surface approximation
We propose an energy-based framework for approximating surfaces from a cloud of point measurements corrupted by noise and outliers. Our energy assigns a tangent plane to each (noi...
Carl Olsson, Yuri Boykov
ICALP
2007
Springer
14 years 2 months ago
Quasi-randomness and Algorithmic Regularity for Graphs with General Degree Distributions
Abstract. We deal with two intimately related subjects: quasi-randomness and regular partitions. The purpose of the concept of quasi-randomness is to measure how much a given graph...
Noga Alon, Amin Coja-Oghlan, Hiêp Hàn...
ICPR
2002
IEEE
14 years 28 days ago
Near-Optimal Regularization Parameters for Applications in Computer Vision
Computer vision requires the solution of many ill-posed problems such as optical flow, structure from motion, shape from shading, surface reconstruction, image restoration and ed...
Changjiang Yang, Ramani Duraiswami, Larry S. Davis
CORR
2010
Springer
188views Education» more  CORR 2010»
13 years 8 months ago
A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers
High-dimensional statistical inference deals with models in which the the number of parameters p is comparable to or larger than the sample size n. Since it is usually impossible ...
Sahand Negahban, Pradeep Ravikumar, Martin J. Wain...