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Full-Text Articles in Physical Sciences and Mathematics
Generalized Mixture Models, Semi-Supervised Learning, And Unknown Class Inference, Samuel J. Frame, Sreenivasa Rao Jammalamadaka
Generalized Mixture Models, Semi-Supervised Learning, And Unknown Class Inference, Samuel J. Frame, Sreenivasa Rao Jammalamadaka
Statistics
In this paper, we discuss generalized mixture models and related semi-supervised learning methods, and show how they can be used to provide explicit methods for unknown class inference. After a brief description of standard mixture modeling and current model-based semi-supervised learning methods, we provide the generalization and discuss its computational implementation using three-stage expectation–maximization algorithm.
Convergent Numerical Scheme For Singular Stochastic Control With State Constraints In A Portfolio Selection Problem, Amarjit Budhiraja, Kevin Ross
Convergent Numerical Scheme For Singular Stochastic Control With State Constraints In A Portfolio Selection Problem, Amarjit Budhiraja, Kevin Ross
Statistics
We consider a singular stochastic control problem with state constraints that arises in problems of optimal consumption and investment under transaction costs. Numerical approximations for the value function using the Markov chain approximation method of Kushner and Dupuis are studied. The main result of the paper shows that the value function of the Markov decision problem (MDP) corresponding to the approximating controlled Markov chain converges to that of the original stochastic control problem as various parameters in the approximation approach suitable limits. All our convergence arguments are probabilistic; the main assumption that we make is that the value function be …