24 citations · 67 across the 9 of their papers we have counts for
5 papers · 1 filter
Model interpretation using improved local regression with variable importance
Gilson Y. Shimizu, Rafael Izbicki, Andre C. P. L. F. de Carvalho
A fundamental question on the use of ML models concerns the explanation of their predictions for increasing transparency in decision-making. Although several interpretability metho…
NLS: an accurate and yet easy-to-interpret regression method
Victor Coscrato, Marco Henrique de Almeida Inácio, Tiago Botari +1
An important feature of successful supervised machine learning applications is to be able to explain the predictions given by the regression or classification model being used. How…
Distance Assessment and Hypothesis Testing of High-Dimensional Samples using Variational Autoencoders
Marco Henrique de Almeida Inácio, Rafael Izbicki, Bálint Gyires-Tóth
Given two distinct datasets, an important question is if they have arisen from the the same data generating function or alternatively how their data generating functions diverge fr…
Conditional independence testing: a predictive perspective
Marco Henrique de Almeida Inácio, Rafael Izbicki, Rafael Bassi Stern
Conditional independence testing is a key problem required by many machine learning and statistics tools. In particular, it is one way of evaluating the usefulness of some features…
Quantification under prior probability shift: the ratio estimator and its extensions
Afonso Fernandes Vaz, Rafael Izbicki, Rafael Bassi Stern
The quantification problem consists of determining the prevalence of a given label in a target population. However, one often has access to the labels in a sample from the training…