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COCOS
2003
Springer
148views Optimization» more  COCOS 2003»
14 years 17 days ago
Convex Programming Methods for Global Optimization
We investigate some approaches to solving nonconvex global optimization problems by convex nonlinear programming methods. We assume that the problem becomes convex when selected va...
John N. Hooker
MOC
1998
96views more  MOC 1998»
13 years 7 months ago
Fast solvers of integral and pseudodifferential equations on closed curves
On the basis of a fully discrete trigonometric Galerkin method and two grid iterations we propose solvers for integral and pseudodifferential equations on closed curves which solv...
Jukka Saranen, Gennadi Vainikko
AI
2011
Springer
12 years 11 months ago
Parallelizing a Convergent Approximate Inference Method
Probabilistic inference in graphical models is a prevalent task in statistics and artificial intelligence. The ability to perform this inference task efficiently is critical in l...
Ming Su, Elizabeth Thompson
CORR
2010
Springer
127views Education» more  CORR 2010»
13 years 7 months ago
Mean field for Markov Decision Processes: from Discrete to Continuous Optimization
We study the convergence of Markov Decision Processes made of a large number of objects to optimization problems on ordinary differential equations (ODE). We show that the optimal...
Nicolas Gast, Bruno Gaujal, Jean-Yves Le Boudec
PE
2000
Springer
101views Optimization» more  PE 2000»
13 years 7 months ago
On the convergence of the power series algorithm
In this paper we study the convergence properties of the power series algorithm, which is a general method to determine (functions of) stationary distributions of Markov chains. W...
Gerard Hooghiemstra, Ger Koole