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SBIA
2010
Springer
15 years 6 months ago
High-Level Modeling of Component-Based CSPs
Most of modern constraint modeling languages combine rich constraint languages with mathematical notations to tackle combinatorial optimization problems. Our purpose is to introduc...
Raphaël Chenouard, Laurent Granvilliers, Rica...
ICASSP
2011
IEEE
14 years 11 months ago
Whole word discriminative point process models
This paper introduces a discriminative extension to whole-word point process modeling techniques. Meant to circumvent the strong independence assumptions of their generative prede...
Aren Jansen
TACAS
2007
Springer
99views Algorithms» more  TACAS 2007»
16 years 1 months ago
"Don't Care" Modeling: A Logical Framework for Developing Predictive System Models
Analysis of biological data often requires an understanding of components of pathways and/or networks and their mutual dependency relationships. Such systems are often analyzed and...
Hillel Kugler, Amir Pnueli, Michael J. Stern, E. J...
MICCAI
2006
Springer
16 years 8 months ago
Improving Segmentation of the Left Ventricle Using a Two-Component Statistical Model
Abstract. Quality of segmentations obtained by 3D Active Appearance Models (AAMs) crucially depends on underlying training data. MRI heart data, however, often come noisy, incomple...
Jirí Hladuvka, Katja Bühler, Sebastian...
IROS
2008
IEEE
211views Robotics» more  IROS 2008»
16 years 2 months ago
GP-BayesFilters: Bayesian filtering using Gaussian process prediction and observation models
Abstract— Bayesian filtering is a general framework for recursively estimating the state of a dynamical system. The most common instantiations of Bayes filters are Kalman filt...
Jonathan Ko, Dieter Fox