New transportation cost inequalities are derived by means of elementary large deviation
reasonings. Their dual characterization is proved; this provides an extension of a well …

This paper gives an algorithm for calculating posterior probabilities using thermodynamic
integration. The thermodynamic integration calculations are accomplished by annealing an …

Artificial intelligence models trained through loss minimization have demonstrated
significant success, grounded in principles from fields like information theory and statistical …

The study of high-dimensional distributions is of interest in probability theory, statistics, and
asymptotic convex geometry, where the object of interest is the uniform distribution on a …

We study the large deviation principle for M-estimators (and maximum likelihood estimators
in particular). We obtain the rate function of the large deviation principle for M-estimators. For …

In this article, we characterize the solutions to a general problem of minimization of an
energy functional under “bad linear constraints, see (3). This badness is a consequence of a …

We describe the organic phase transfer of surfactant-stabilized rhodium nanoparticles
previously synthesized in an aqueous solution of N, N-dimethyl-N-dodecyl-N-(2 …

We consider Coulomb gas models for which the empirical measure typically concentrates,
when the number of particles becomes large, on an equilibrium measure minimizing an …

This paper deals with order identification for nested models in the iid framework. We study
the asymptotic efficiency of two generalized likelihood ratio tests of the order. They are …

Entropic projections and dominating points are solutions to convex minimization problems
related to conditional laws of large numbers. They appear in many areas of applied …