339 citations · 551 across the 39 of their papers we have counts for
10 papers · 1 filter
Adaptive Bayesian SLOPE -- High-dimensional Model Selection with Missing Values
Wei Jiang, Malgorzata Bogdan, Julie Josse +3
We consider the problem of variable selection in high-dimensional settings with missing observations among the covariates. To address this relatively understudied problem, we propo…
Jaccard/Tanimoto similarity test and estimation methods
Neo Christopher Chung, Błażej Miasojedow, Michał Startek +1
Binary data are used in a broad area of biological sciences. Using binary presence-absence data, we can evaluate species co-occurrences that help elucidate relationships among orga…
Sparse estimation in Ising Model via penalized Monte Carlo methods
Błażej Miasojedow, Wojciech Rejchel
We consider a problem of model selection in high-dimensional binary Markov random fields. The usefulness of the Ising model in studying systems of complex interactions has been con…
Geometric ergodicity of Rao and Teh's algorithm for Markov jump processes
Błażej Miasojedow, Wojciech Niemiro
Rao and Teh (2013) introduced an efficient MCMC algorithm for sampling from the posterior distribution of a hidden Markov jump process. The algorithm is based on the idea of sampli…
Asymptotics of Monte Carlo maximum likelihood estimators
Blazej Miasojedow, Wojciech Niemiro, Jan Palczewski +1
We describe Monte Carlo approximation to the maximum likelihood estimator in models with intractable norming constants and explanatory variables. We consider both sources of random…
Adaptive Monte Carlo Maximum Likelihood
Blazej Miasojedow, Wojciech Niemiro, Jan Palczewski +1
We consider Monte Carlo approximations to the maximum likelihood estimator in models with intractable norming constants. This paper deals with adaptive Monte Carlo algorithms, whic…
Metropolis-type algorithms for Continuous Time Bayesian Networks
Blazej Miasojedow, Wojciech Niemiro, John Noble +1
We present a Metropolis-Hastings Markov chain Monte Carlo (MCMC) algorithm for detecting hidden variables in a continuous time Bayesian network (CTBN), which uses reversible jumps…
Optimal scaling for the transient phase of Metropolis Hastings algorithms: The longtime behavior
Benjamin Jourdain, Tony Lelièvre, Błażej Miasojedow
We consider the Random Walk Metropolis algorithm on with Gaussian proposals, and when the target probability measure is the -fold product of a one-dimensional law…
Nonasymptotic bounds on the estimation error of MCMC algorithms
Krzysztof Łatuszyński, Błażej Miasojedow, Wojciech Niemiro
We address the problem of upper bounding the mean square error of MCMC estimators. Our analysis is nonasymptotic. We first establish a general result valid for essentially all ergo…
Nonasymptotic bounds on the estimation error for regenerative MCMC algorithms
Krzysztof Latuszynski, Blazej Miasojedow, Wojciech Niemiro
MCMC methods are used in Bayesian statistics not only to sample from posterior distributions but also to estimate expectations. Underlying functions are most often defined on a con…