Zobrazeno 1 - 10
of 111
pro vyhledávání: '"Manolopoulou, Ioanna"'
Rating procedure is crucial in many applied fields (e.g., educational, clinical, emergency). It implies that a rater (e.g., teacher, doctor) rates a subject (e.g., student, doctor) on a rating scale. Given raters variability, several statistical meth
Externí odkaz:
http://arxiv.org/abs/2410.21498
In several observational contexts where different raters evaluate a set of items, it is common to assume that all raters draw their scores from the same underlying distribution. However, a plenty of scientific works have evidenced the relevance of in
Externí odkaz:
http://arxiv.org/abs/2309.15076
In this paper, we address the challenge of performing counterfactual inference with observational data via Bayesian nonparametric regression adjustment, with a focus on high-dimensional settings featuring multiple actions and multiple correlated outc
Externí odkaz:
http://arxiv.org/abs/2211.11119
In this extended abstract paper, we address the problem of interpretability and targeted regularization in causal machine learning models. In particular, we focus on the problem of estimating individual causal/treatment effects under observed confoun
Externí odkaz:
http://arxiv.org/abs/2206.10261
Autor:
Carrasco, Mariflor Vega, Musolesi, Mirco, O'Sullivan, Jason, Prior, Rosie, Manolopoulou, Ioanna
Understanding the customer behaviours behind transactional data has high commercial value in the grocery retail industry. Customers generate millions of transactions every day, choosing and buying products to satisfy specific shopping needs. Product
Externí odkaz:
http://arxiv.org/abs/2111.08078
This paper develops a sparsity-inducing version of Bayesian Causal Forests, a recently proposed nonparametric causal regression model that employs Bayesian Additive Regression Trees and is specifically designed to estimate heterogeneous treatment eff
Externí odkaz:
http://arxiv.org/abs/2102.06573
Large observational data are increasingly available in disciplines such as health, economic and social sciences, where researchers are interested in causal questions rather than prediction. In this paper, we examine the problem of estimating heteroge
Externí odkaz:
http://arxiv.org/abs/2009.06472
Autor:
Vega-Carrasco, Mariflor, O'sullivan, Jason, Prior, Rosie, Manolopoulou, Ioanna, Musolesi, Mirco
Understanding the shopping motivations behind market baskets has high commercial value in the grocery retail industry. Analyzing shopping transactions demands techniques that can cope with the volume and dimensionality of grocery transactional data w
Externí odkaz:
http://arxiv.org/abs/2005.10125
Akademický článek
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Publikováno v:
A&A 630, A117 (2019)
In studies of the interstellar medium in galaxies, radiative transfer models of molecular emission are useful for relating molecular line observations back to the physical conditions of the gas they trace. However, doing this requires solving a highl
Externí odkaz:
http://arxiv.org/abs/1907.07472