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ICML
2007
IEEE
14 years 10 months ago
Efficiently computing minimax expected-size confidence regions
Given observed data and a collection of parameterized candidate models, a 1- confidence region in parameter space provides useful insight as to those models which are a good fit t...
Brent Bryan, H. Brendan McMahan, Chad M. Schafer, ...
ECCV
2010
Springer
14 years 2 months ago
Cosegmentation revisited: Models and optimization
The problem of cosegmentation consists of segmenting the same object (or objects of the same class) in two or more distinct images. Recently a number of different models have been...
CORR
2010
Springer
207views Education» more  CORR 2010»
13 years 10 months ago
Collaborative Hierarchical Sparse Modeling
Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an 1-regularized linear regression prob...
Pablo Sprechmann, Ignacio Ramírez, Guillerm...
CORR
2006
Springer
82views Education» more  CORR 2006»
13 years 10 months ago
Explicit Randomness is not Necessary when Modeling Probabilistic Encryption
Although good encryption functions are probabilistic, most symbolic models do not capture this aspect explicitly. A typical solution, recently used to prove the soundness of such ...
Véronique Cortier, Heinrich Hördegen, ...
IROS
2007
IEEE
186views Robotics» more  IROS 2007»
14 years 4 months ago
3D forward sensor modeling and application to occupancy grid based sensor fusion
— This paper presents a new technique for the update of a probabilistic spatial occupancy grid map using a forward sensor model. Unlike currently popular inverse sensor models, f...
Kaustubh Pathak, Andreas Birk 0002, Jann Poppinga,...