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Found 3 papers, 2 papers with code
Adaptive Bayesian SLOPE -- High-dimensional Model Selection with Missing Values
We consider the problem of variable selection in high-dimensional settings with missing observations among the covariates.
Methodology Applications Computation
Non-asymptotic Analysis of Biased Stochastic Approximation Scheme
We illustrate these settings with the online EM algorithm and the policy-gradient method for average reward maximization in reinforcement learning.
Adaptive parallel tempering algorithm
Parallel tempering is a generic Markov chain Monte Carlo sampling method which allows good mixing with multimodal target distributions, where conventional Metropolis-Hastings algorithms often fail.
Computation
