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 …

Concentration of tempered posteriors and of their variational approximations Page 1 The
Annals of Statistics 2020, Vol. 48, No. 3, 1475–1497 https://doi.org/10.1214/19-AOS1855 © …

Supplement to “Consistency of variational Bayes inference for estimation and model
selection in mixtures”. The supplementary material zip contains the description of a short …

Supplementary material to “Estimation bounds and sharp oracle inequalities of regularized
procedures with Lipschitz loss functions”. In the supplementary material, we provide a …

We consider the properties of a specific distribution of mixed quantum states of arbitrary
dimension that can be biased towards a specific mean purity. In particular, we analyze …

Recently, there has been a significant focus on exploring the theoretical aspects of deep
learning, especially regarding its performance in classification tasks. Bayesian deep …

This paper investigates the problem of simultaneously predicting multiple binary responses
by utilizing a shared set of covariates. Our approach incorporates machine learning …

Bayesian inference provides an attractive online-learning framework to analyze sequential
data, and offers generalization guarantees which hold even with model mismatch and …

In this paper, we study the problem of bilinear regression, a type of statistical modeling that
deals with multiple variables and multiple responses. One of the main difficulties that arise in …

Entropy | Free Full-Text | Approximate Bayesian Inference Next Article in Journal Minimum
Spanning vs. Principal Trees for Structured Approximations of Multi-Dimensional Datasets …