Modified Cholesky Riemann Manifold Hamiltonian Monte Carlo: exploiting sparsity for fast sampling of high-dimensional targets.
Tore Selland KleppePublished in: Stat. Comput. (2018)
Keyphrases
- monte carlo
- high dimensional
- low dimensional
- importance sampling
- adaptive sampling
- manifold learning
- parameter space
- markov chain
- data points
- monte carlo simulation
- dimensionality reduction
- feature space
- monte carlo methods
- point processes
- high dimensional data
- particle filter
- markov chain monte carlo
- matrix inversion
- monte carlo tree search
- euclidean space
- variance reduction
- variable selection
- sample size
- stochastic approximation
- training samples
- input space
- random sampling
- optimal strategy
- game tree
- kernel function