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Found 7 papers, 2 papers with code
Differentially Private Range Queries with Correlated Input Perturbation
This work proposes a class of locally differentially private mechanisms for linear queries, in particular range queries, that leverages correlated input perturbation to simultaneously achieve unbiasedness, consistency, statistical transparency, and control over utility requirements in terms of accuracy targets expressed either in certain query margins or as implied by the hierarchical database structure.
Optimal randomized multilevel Monte Carlo for repeatedly nested expectations
Fix any non-negative integer $D$ for the total number of nestings.
Metropolis-Hastings transition kernel couplings
Couplings play a central role in the analysis of Markov chain convergence and in the construction of novel Markov chain Monte Carlo estimators, diagnostics, and variance reduction techniques.
Statistics Theory Probability Computation Statistics Theory 60J22, 65C05, 62D05
On the Theoretical Properties of the Exchange Algorithm
or `Does the exchange algorithm admit a Central Limit Theorem?'
Modeling treatment events in disease progression
Ability to quantify and predict progression of a disease is fundamental for selecting an appropriate treatment.
A Fast MCMC for the Uniform Sampling of Binary Matrices with Fixed Margins
Uniform sampling of binary matrix with fixed margins is an important and difficult problem in statistics, computer science, ecology and so on.
Computation Data Structures and Algorithms Combinatorics Applications
A Multi-armed Bandit MCMC, with applications in sampling from doubly intractable posterior
Markov chain Monte Carlo (MCMC) algorithms are widely used to sample from complicated distributions, especially to sample from the posterior distribution in Bayesian inference.
