4 papers
Variance-Aware Estimation of Kernel Mean Embedding
Geoffrey Wolfer, Pierre Alquier
An important feature of kernel mean embeddings (KME) is that the rate of convergence of the empirical KME to the true distribution KME can be bounded independently of the dimension…
User-friendly introduction to PAC-Bayes bounds
Pierre Alquier
Aggregated predictors are obtained by making a set of basic predictors vote according to some weights, that is, to some probability distribution. Randomized predictors are obtained…
Finite sample properties of parametric MMD estimation: robustness to misspecification and dependence
Badr-Eddine Chérief-Abdellatif, Pierre Alquier
Many works in statistics aim at designing a universal estimation procedure, that is, an estimator that would converge to the best approximation of the (unknown) data generating dis…
Concentration of discrepancy-based approximate Bayesian computation via Rademacher complexity
Sirio Legramanti, Daniele Durante, Pierre Alquier
There has been increasing interest on summary-free solutions for approximate Bayesian computation (ABC) which replace distances among summaries with discrepancies between the empir…