webinars

Developments in Bayesian Nonparametrics

2021-04-06

The second “One World webinar” organized by YoungStatS will take place on April 21st. The focus of this webinar will be on illustrating modern advances in Bayesian Nonparametrics data analysis, discussing challenging theoretical problems and stimulating case-studies within this active…

machine-learning

Analysis of a Two-Layer Neural Network via Displacement Convexity

Adel Javanmard, Marco Mondelli and Andrea Montanari / 2021-03-14

We consider the problem of learning a function defined on a compact domain, using linear combinations of a large number of “bump-like” components (neurons). This idea lies at the core of a variety of methods from two-layer neural networks to kernel regression, to boosting. In general, the resulting…

generalized-linear-models

A Scalable Empirical Bayes Approach to Variable Selection in Generalized Linear Models

Haim Bar, James Booth and Martin T. Wells / 2021-03-13

In the toolbox of most scientists over the past century, there have been few methods as powerful and as versatile as linear regression. The introduction of the generalized linear model (GLM) framework in the 1970’s extended the inferential and predictive capabilities to binary or count data. While…

compositional data

Compositional scalar-on-function regression as a tool (not only) for geological data

Ivana Pavlů, Karel Hron / 2021-03-10

Compositional data are characterized by the fact that the relevant information is contained not necessarily in the absolute values but rather in the relative proportions between particular components. As an example, take household expenditures for different purposes (housing, groceries, travel etc.)…

maximum-likelihood

Higher Order Targeted Maximum Likelihood Estimation

Zeyi Wang and Mark van der Laan / 2021-03-10

Summary We propose a higher order targeted maximum likelihood estimation (TMLE) that only relies on a sequentially and recursively defined set of data-adaptive fluctuations. Without the need to assume the often too stringent higher order pathwise differentiability, the method is practical for…

compositional data

Give me an adequate correlation: assessing relationships in percentage (or proportional) data

Karel Hron, Peter Filzmoser / 2021-02-04

We assume that you are quite familiar with the following problem. Consider a data set where the information is expressed in percentages or proportions. An example are household expenditures, given as average amounts (in Euros) the households are spending on food, housing, transportation, etc. Since…