2 citations · 2 across the 4 of their papers we have counts for
5 papers
Convergence of a class of gradient-free optimisation schemes when the objective function is noisy, irregular, or both
Christophe Andrieu, Nicolas Chopin, Ettore Fincato +1
We investigate the convergence properties of a class of iterative algorithms designed to minimize a potentially non-smooth and noisy objective function, which may be algebraically…
On the unconventional Hug integrator
Christophe Andrieu, J. M. Sanz-Serna
Hug is a recently proposed iterative mapping used to design efficient updates in Markov chain Monte Carlo (MCMC) methods. Hug generates proposals that remain very close to hypersur…
Self-Organizing State-Space Models with Artificial Dynamics
Yuan Chen, Mathieu Gerber, Christophe Andrieu +1
We consider the problem of performing parameter and state inference in a state-space model (SSM) parametrized by a static parameter . A popular idea to address this problem cons…
Gradient-free optimization via integration
Christophe Andrieu, Nicolas Chopin, Ettore Fincato +1
We develop and analyse an approach to optimize functions not assumed to be convex, differentiable or even continuous. The algorithm be…
Monte Carlo sampling with integrator snippets
Christophe Andrieu, Mauro Camara Escudero, Chang Zhang
Assume interest is in sampling from a probability distribution defined on . We develop a framework for sampling algorithms which takes full advantage…