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ESANN
2003
15 years 2 months ago
On Convergence Problems of the EM Algorithm for Finite Gaussian Mixtures
Efficient probability density function estimation is of primary interest in statistics. A popular approach for achieving this is the use of finite Gaussian mixture models. Based on...
Cédric Archambeau, John Aldo Lee, Michel Ve...
ADCM
2007
114views more  ADCM 2007»
15 years 1 months ago
Convergence analysis of online algorithms
In this paper, we are interested in the analysis of regularized online algorithms associated with reproducing kernel Hilbert spaces. General conditions on the loss function and st...
Yiming Ying
CCE
2004
15 years 1 months ago
Improving convergence of the stochastic decomposition algorithm by using an efficient sampling technique
This work focuses on the basic stochastic decomposition (SD) algorithm of Higle and Sen [J.L. Higle, S. Sen, Stochastic Decomposition, Kluwer Academic Publishers, 1996] for two-st...
José María Ponce-Ortega, Vicente Ric...
124
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ICML
1996
IEEE
15 years 5 months ago
A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Rémi Munos
PPSN
1994
Springer
15 years 5 months ago
Convergence Models of Genetic Algorithm Selection Schemes
We discuss the use of normal distribution theory as a tool to model the convergence characteristics of di erent GA selection schemes. The models predict the proportion of optimal a...
Dirk Thierens, David E. Goldberg