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ICASSP
2011
IEEE
12 years 11 months ago
Langevin and hessian with fisher approximation stochastic sampling for parameter estimation of structured covariance
We have studied two efficient sampling methods, Langevin and Hessian adapted Metropolis Hastings (MH), applied to a parameter estimation problem of the mathematical model (Lorent...
Cornelia Vacar, Jean-François Giovannelli, ...
JMLR
2006
136views more  JMLR 2006»
13 years 7 months ago
Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis
In this paper we consider a novel Bayesian interpretation of Fisher's discriminant analysis. We relate Rayleigh's coefficient to a noise model that minimises a cost base...
Tonatiuh Peña Centeno, Neil D. Lawrence
GECCO
2008
Springer
132views Optimization» more  GECCO 2008»
13 years 8 months ago
Hybridizing an evolutionary algorithm with mathematical programming techniques for multi-objective optimization
In recent years, the development of multi-objective evolutionary algorithms (MOEAs) hybridized with mathematical programming techniques has significantly increased. However, most...
Saúl Zapotecas Martínez, Carlos A. C...
EOR
2010
88views more  EOR 2010»
13 years 7 months ago
Mathematical programming approaches for generating p-efficient points
Abstract: Probabilistically constrained problems, in which the random variables are finitely distributed, are nonconvex in general and hard to solve. The p-efficiency concept has b...
Miguel A. Lejeune, Nilay Noyan
MP
2007
102views more  MP 2007»
13 years 7 months ago
Elastic-mode algorithms for mathematical programs with equilibrium constraints: global convergence and stationarity properties
The elastic-mode formulation of the problem of minimizing a nonlinear function subject to equilibrium constraints has appealing local properties in that, for a finite value of the...
Mihai Anitescu, Paul Tseng, Stephen J. Wright