Sciweavers

Share
298 search results - page 1 / 60
» Approximate Inference and Constrained Optimization
Sort
View
UAI
2003
12 years 1 months ago
Approximate Inference and Constrained Optimization
Loopy and generalized belief propagation are popular algorithms for approximate inference in Markov random fields and Bayesian networks. Fixed points of these algorithms correspo...
Tom Heskes, Kees Albers, Bert Kappen
INFOCOM
2009
IEEE
12 years 6 months ago
Prize-Collecting Data Fusion for Cost-Performance Tradeoff in Distributed Inference
—A novel formulation for optimal sensor selection and in-network fusion for distributed inference known as the prizecollecting data fusion (PCDF) is proposed in terms of optimal ...
Animashree Anandkumar, Meng Wang, Lang Tong, Anant...
CVPR
2009
IEEE
13 years 6 months ago
Convexity and Bayesian Constrained Local Models
The accurate localization of facial features plays a fundamental role in any face recognition pipeline. Constrained local models (CLM) provide an effective approach to localizati...
Ulrich Paquet (Imense Ltd)
CDC
2010
IEEE
151views Control Systems» more  CDC 2010»
11 years 6 months ago
Convergence of discrete-time approximations of constrained linear-quadratic optimal control problems
Abstract-- Continuous-time linear constrained optimal control problems are in practice often solved using discretization techniques, e.g. in model predictive control (MPC). This re...
Lanshan Han, M. Kanat Camlibel, Jong-Shi Pang, W. ...
PPSN
2004
Springer
12 years 5 months ago
Constrained Evolutionary Optimization by Approximate Ranking and Surrogate Models
Abstract. The paper describes an evolutionary algorithm for the general nonlinear programming problem using a surrogate model. Surrogate models are used in optimization when model ...
Thomas Philip Runarsson
books