Actualités
All About that Bayes
Prochaine séance - 21 Mars 2023, 14:00,AgroParisTech (22 place de l'Agronomie, 91123 Palaiseau. Francesca Crucinio (ENSAE) - Optimal Scaling Results for a Wide Class of Proximal MALA Algorithms.
Abstract. We consider a recently proposed class of MCMC methods which uses proximity maps instead of gradients to build proposal mechanisms which can be employed for both differentiable and non-differentiable targets. These methods have been shown to be stable for a wide class of targets, making them a valuable alternative to Metropolis-adjusted Langevin algorithms (MALA); and have found wide application in imaging contexts. The wider stability properties are obtained by building the Moreau-Yoshida envelope for the target of interest, which depends on a parameter $\lambda$. In this work, we investigate the optimal scaling problem for this class of algorithms, which encompasses MALA, and provide practical guidelines for the implementation of these methods.
Joint work with Alain Durmus, Pablo Jiménez, Gareth O. Roberts.
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