203 citations · 1.6k across the 78 of their papers we have counts for
6 papers · 1 filter
A probabilistic incremental proximal gradient method
Ömer Deniz Akyildiz, Émilie Chouzenoux, Víctor Elvira +1
In this paper, we propose a probabilistic optimization method, named probabilistic incremental proximal gradient (PIPG) method, by developing a probabilistic interpretation of the…
Rethinking the Effective Sample Size
Víctor Elvira, Luca Martino, Christian P. Robert
The effective sample size (ESS) is widely used in sample-based simulation methods for assessing the quality of a Monte Carlo approximation of a given distribution and of related in…
The Incremental Proximal Method: A Probabilistic Perspective
Ömer Deniz Akyildiz, Victor Elvira, Joaquin Miguez
In this work, we highlight a connection between the incremental proximal method and stochastic filters. We begin by showing that the proximal operators coincide, and hence can be r…
Robust Covariance Adaptation in Adaptive Importance Sampling
Yousef El-Laham, Victor Elvira, Monica F. Bugallo
Importance sampling (IS) is a Monte Carlo methodology that allows for approximation of a target distribution using weighted samples generated from another proposal distribution. Ad…
Accelerating MCMC Algorithms
Christian P. Robert, Victor Elvira, Nick Tawn +1
Markov chain Monte Carlo algorithms are used to simulate from complex statistical distributions by way of a local exploration of these distributions. This local feature avoids heav…
Pattern Localization in Time Series through Signal-To-Model Alignment in Latent Space
Steven Van Vaerenbergh, Ignacio Santamaria, Victor Elvira +1
In this paper, we study the problem of locating a predefined sequence of patterns in a time series. In particular, the studied scenario assumes a theoretical model is available tha…