A generalized framework for development of partially-updated signal and parameter estimation algorithms based on subspace optimization constraints.
Brian G. AgeePublished in: ACSSC (2013)
Keyphrases
- parameter estimation
- optimization problems
- least squares
- estimation problems
- constrained optimization
- model selection
- parameter optimization
- maximum likelihood
- em algorithm
- markov chain monte carlo
- maximum likelihood estimation
- markov random field
- parameter estimation algorithm
- statistical models
- parameter values
- random fields
- model fitting
- high dimensional
- dynamic model
- experimental data
- expectation maximization
- bayesian model selection
- stochastic logic programs
- metropolis hastings algorithm