Feature Selection based on the Local Lift Dependence Scale. - Diego Marcondes; Adilson Simonis; Junior Barrera (Entropy, 2018)

Learning the hypotheses space from data through a U-curve algorithm: a statistically consistent complexity regularizer for Model Selection. - Diego Marcondes; Adilson Simonis; Junior Barrera (CoRR, 2021)

A snapshot of a pandemic: The interplay between social isolation and COVID-19 dynamics in Brazil. - Cláudia Pio Ferreira; Diego Marcondes; Mariana P. Melo; Sérgio M. Oliva; Cláudia M. Peixoto; Pedro S. Peixoto (Patterns, 2021)

The role of prior information and computational power in Machine Learning. - Diego Marcondes; Adilson Simonis; Junior Barrera (CoRR, 2022)

Distribution-free Deviation Bounds of Learning via Model Selection with Cross-validation Risk Estimation. - Diego Marcondes; Cláudia M. Peixoto (CoRR, 2023)

The Lattice Overparametrization Paradigm for the Machine Learning of Lattice Operators. - Diego Marcondes; Junior Barrera (DGMM, 2024)

An Algorithm to Train Unrestricted Sequential Discrete Morphological Neural Networks. - Diego Marcondes; Mariana Feldman; Junior Barrera (DGMM, 2024)

Generalized Resubstitution for Regression Error Estimation. - Diego Marcondes; Ulisses Braga-Neto (CoRR, 2024)

Back to basics to open the black box. - Diego Marcondes; Adilson Simonis; Junior Barrera (Nat. Mac. Intell., 2024)

Discrete Morphological Neural Networks. - Diego Marcondes; Junior Barrera (SIAM J. Imaging Sci., 2024)

On the Representation of Stack Operators by Mathematical Morphology. - Diego Marcondes (DGMM, 2025)

Unrestricted Sequential Discrete Morphological Neural Networks. - Diego Marcondes; Mariana Feldman; Junior Barrera (J. Math. Imaging Vis., 2025)

Complexity Dependent Error Rates for Physics-informed Statistical Learning via the Small-ball Method. - Diego Marcondes (CoRR, 2025)