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ICML
2007
IEEE
15 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
15 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»
14 years 9 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»
14 years 9 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»
15 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,...