49 citations · 138 across the 18 of their papers we have counts for
18 papers
Minimax Quasi-Bayesian estimation in sparse canonical correlation analysis via a Rayleigh quotient function
Qiuyun Zhu, Yves Atchade
Canonical correlation analysis (CCA) is a popular statistical technique for exploring relationships between datasets. In recent years, the estimation of sparse canonical vectors ha…
Bayesian Analysis of High-dimensional Discrete Graphical Models
Anwesha Bhattacharyya, Yves Atchade
This work introduces a Bayesian methodology for fitting large discrete graphical models with spike-and-slab priors to encode sparsity. We consider a quasi-likelihood approach that…
Sequential change-point detection in high-dimensional Gaussian graphical models
Hossein Keshavarz, George Michailidis, Yves Atchade
High dimensional piecewise stationary graphical models represent a versatile class for modelling time varying networks arising in diverse application areas, including biology, econ…
An approach to large-scale Quasi-Bayesian inference with spike-and-slab priors
Yves Atchade, Anwesha Bhattacharyya
We propose a general framework using spike-and-slab prior distributions to aid with the development of high-dimensional Bayesian inference. Our framework allows inference with a ge…
Automatic adaptation of MCMC algorithms
Dao Nguyen, Perry de Valpine, Yves Atchade +3
Markov chain Monte Carlo (MCMC) methods are ubiquitous tools for simulation-based inference in many fields but designing and identifying good MCMC samplers is still an open questio…
Likelihood Inference for Large Scale Stochastic Blockmodels with Covariates based on a Divide-and-Conquer Parallelizable Algorithm with Communication
Sandipan Roy, Yves Atchadé, George Michailidis
We consider a stochastic blockmodel equipped with node covariate information, that is helpful in analyzing social network data. The key objective is to obtain maximum likelihood es…