Polynomial time guarantees for sampling based posterior inference in high-dimensional generalised linear models.
Randolf AltmeyerPublished in: CoRR (2022)
Keyphrases
- linear models
- variable selection
- high dimensional
- markov chain monte carlo
- additive models
- gaussian processes
- parameter estimation
- linear model
- linear regression
- bayesian inference
- posterior distribution
- model selection
- cross validation
- low dimensional
- dimension reduction
- dimensionality reduction
- computational complexity
- gaussian process
- probabilistic inference
- bayesian networks
- probabilistic model
- worst case
- high dimensionality
- high dimensional data
- bayesian framework
- least squares
- data points
- feature space
- knn
- probability distribution
- machine learning
- causal relationships
- regression model
- nonlinear models