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Found 10 papers, 2 papers with code
De-Sequentialized Monte Carlo: a parallel-in-time particle smoother
We propose dSMC (de-Sequentialized Monte Carlo), a new particle smoother that is able to process $T$ observations in $\mathcal{O}(\log T)$ time on parallel architecture.
Computational Doob's h-transforms for Online Filtering of Discretely Observed Diffusions
This paper is concerned with online filtering of discretely observed nonlinear diffusion processes.
Modelling dependency completion in sentence comprehension as a Bayesian hierarchical mixture process: A case study involving Chinese relative clauses
We present a case-study demonstrating the usefulness of Bayesian hierarchical mixture modelling for investigating cognitive processes.
On the properties of variational approximations of Gibbs posteriors
We consider instead variational approximations of the Gibbs posterior, which are fast to compute.
The Poisson transform for unnormalised statistical models
Here we show that inferring the parameters of a unnormalised model on a space $\Omega$ can be mapped onto an equivalent problem of estimating the intensity of a Poisson point process on $\Omega$.
Bayesian matrix completion: prior specification
While the behaviour of algorithms based on nuclear norm minimization is now well understood, an as yet unexplored avenue of research is the behaviour of Bayesian algorithms in this context.
PAC-Bayesian AUC classification and scoring
We also extend our method to a class of non-linear score functions, essentially leading to a nonparametric procedure, by considering a Gaussian process prior.
PAC-Bayesian Offline Contextual Bandits With Guarantees
This paper introduces a new principled approach for off-policy learning in contextual bandits.
Fast Slate Policy Optimization: Going Beyond Plackett-Luce
We compare our method to the commonly adopted Plackett-Luce policy class and demonstrate the effectiveness of our approach on problems with action space sizes in the order of millions.
A connection between Tempering and Entropic Mirror Descent
We establish that tempering SMC corresponds to entropic mirror descent applied to the reverse Kullback-Leibler (KL) divergence and obtain convergence rates for the tempering iterates.
