CREST Working Papers Series No. 2017-41
by Alexandra Carpentier, Olga Klopp and Matthias Löffler
Improving approximate Bayesian computation via quasi Monte Carlo
CREST Working Papers Series No. 2017-37
by Alexander Buchholz and Nicolas Chopin
Negative association, ordering and convergence of resampling methods
CREST Working Papers Series No. 2017-36
by Mathieu Gerber, Nicolas Chopin and Nick Whiteley
Sequential quasi-Monte Carlo: Introduction for Non-Experts, Dimension Reduction, Application to Partly Observed Diffusion Processes
CREST Working Papers Series No. 2017-35
by Nicolas Chopin and Mathieu Gerber
Modelling dependency completion in sentence comprehension as a Bayesian hierarchical mixture process: A case study involving Chinese relative clauses
CREST Working Papers Series No. 2017-34
by Shravan Vasishth, Nicolas Chopin, Robin Ryder and Bruno Nicenboim
Bayesian Hierarchical Finite Mixture Models of Reading Times: A Case Study
CREST Working Papers Series No. 2017-33
by Shravan Vasishth, Bruno Nicenboim, Nicolas Chopin and Robin Ryder
Robust machine learning by median-of-means : theory and practice
CREST Working Papers Series No. 2017-32
by Guillaume Lecué and Mathieu Lerasle
An IHT algorithm for sparse recovery from subexponential measurements
CREST Working Papers Series No. 2017-31
by Simon Foucart and Guillaume Lecué
Estimation bounds and sharp oracle inequalities of regularized procedures with Lipschitz loss functions
CREST Working Papers Series No. 2017-30
by Pierre Alquier, Vincent Cottet and Guillaume Lecué