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JMLR
2010
148views more  JMLR 2010»
14 years 4 months ago
Approximate Inference on Planar Graphs using Loop Calculus and Belief Propagation
We introduce novel results for approximate inference on planar graphical models using the loop calculus framework. The loop calculus (Chertkov and Chernyak, 2006b) allows to expre...
Vicenç Gómez, Hilbert J. Kappen, Mic...
ICML
2008
IEEE
15 years 10 months ago
Boosting with incomplete information
In real-world machine learning problems, it is very common that part of the input feature vector is incomplete: either not available, missing, or corrupted. In this paper, we pres...
Feng Jiao, Gholamreza Haffari, Greg Mori, Shaojun ...
MODELS
2009
Springer
15 years 4 months ago
Feature-oriented programming with Ruby
Features identify core characteristics of software in order to produce families of programs. Through configuration, different variants of a program can be composed. Our approach...
Sebastian Günther, Sagar Sunkle
CVPR
2007
IEEE
15 years 11 months ago
Efficient Belief Propagation for Vision Using Linear Constraint Nodes
Belief propagation over pairwise connected Markov Random Fields has become a widely used approach, and has been successfully applied to several important computer vision problems....
Brian Potetz
ICASSP
2011
IEEE
14 years 27 days ago
Weighted and structured sparse total least-squares for perturbed compressive sampling
Solving linear regression problems based on the total least-squares (TLS) criterion has well-documented merits in various applications, where perturbations appear both in the data...
Hao Zhu, Georgios B. Giannakis, Geert Leus