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Piecewise Deterministic Monte Carlo algorithms enable simulation from a posterior distribution, whilst only needing to access a sub-sample of data at each iteration.
Simulation of nonhomogeneous Poisson processes by thinning
P. A. Lewis and G. S. Shedler · 1979
Earlier work this paper cites.
Piecewise-deterministic Markov processes: A general class of non-diffusion stochastic models
M. H. A. Davis · 1984
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Exact inference in the inequality constrained normal linear regression model
J. Geweke · 1986
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Bayesian analysis of binary and polychotomous response data
J. H. Albert and S. Chib · 1993
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Analysis of a nonreversible Markov chain sampler
P. Diaconis, S. Holmes, and R. Neal · 2000
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Multivariate Statistical Modelling based on Generalized Linear Models
L. Fahrmeir and G. Tutz · 2001
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An interior point Newton-like method for non-negative least-squares problems with degenerate solution
S. Bellavia, M. Macconi, and B. Morini · 2006
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Sparse non-negative matrix factorizations via alternating non-negativity-constrained least squares for microarray data analysis
H. Kim and H. Park · 2007
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Discrete Choice Methods with Simulation
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Irreversible Monte Carlo algorithms for efficient sampling
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Rejection-free Monte Carlo sampling for general potentials
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Stochastic gradient Riemannian Langevin dynamics on the probability simplex
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Exact Hamiltonian Monte Carlo for truncated multivariate Gaussians
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Event-chain algorithm for the Heisenberg model
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The Zig-Zag process and super-efficient sampling for Bayesian analysis of big data
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Piecewise deterministic Markov processes for continuous-time Monte Carlo
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On Event-Chain Monte Carlo Methods
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Stochastic bouncy particle sampler
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Rating scales as predictors—the old question of scale level and some answers
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