5 citations · 5 across the 1 of their papers we have counts for
4 papers
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…
The NN-Stacking: Feature weighted linear stacking through neural networks
Victor Coscrato, Marco Henrique de Almeida Inácio, Rafael Izbicki
Stacking methods improve the prediction performance of regression models. A simple way to stack base regressions estimators is by combining them linearly, as done by \citet{breiman…