A Markov Chain Genetic Algorithm Approach for Non-Parametric Posterior Distribution Sampling of Regression Parameters.
Parag C. PendharkarPublished in: Algorithms (2024)
Keyphrases
- markov chain
- posterior distribution
- gibbs sampler
- markov chain monte carlo
- monte carlo method
- parameter estimation
- hyperparameters
- genetic algorithm
- prior distribution
- model selection
- gaussian processes
- transition probabilities
- importance sampling
- monte carlo
- probability distribution
- gibbs sampling
- bayesian framework
- bayesian learning
- gaussian process
- random sampling
- support vector
- latent variables
- bayesian inference
- expectation maximization
- markov chain monte carlo methods
- maximum a posteriori
- random fields
- maximum likelihood
- least squares
- cross validation
- sample size
- generalized gaussian
- random walk
- state space
- generative model
- incremental learning
- regression model
- approximate inference
- probability density function
- probabilistic model
- feature selection
- parameter settings
- parameter values
- posterior probability
- parameter space
- prior information
- em algorithm
- noise level
- gaussian distribution
- image reconstruction
- genetic algorithm ga
- prior model
- training data