9 citations · 17 across the 6 of their papers we have counts for
8 papers
From Actions to Events: A Transfer Learning Approach Using Improved Deep Belief Networks
Mateus Roder, Jurandy Almeida, Gustavo H. de Rosa +3
In the last decade, exponential data growth supplied machine learning-based algorithms' capacity and enabled their usage in daily-life activities. Additionally, such an improvement…
Comparative Study Between Distance Measures On Supervised Optimum-Path Forest Classification
Gustavo Henrique de Rosa, Mateus Roder, João Paulo Papa
Machine Learning has attracted considerable attention throughout the past decade due to its potential to solve far-reaching tasks, such as image classification, object recognition,…
Speeding Up OPFython with Numba
Gustavo H. de Rosa, João Paulo Papa
A graph-inspired classifier, known as Optimum-Path Forest (OPF), has proven to be a state-of-the-art algorithm comparable to Logistic Regressors, Support Vector Machines in a wide…
Energy-based Dropout in Restricted Boltzmann Machines: Why not go random
Mateus Roder, Gustavo H. de Rosa, Victor Hugo C. de Albuquerque +2
Deep learning architectures have been widely fostered throughout the last years, being used in a wide range of applications, such as object recognition, image reconstruction, and s…
A Nature-Inspired Feature Selection Approach based on Hypercomplex Information
Gustavo H. de Rosa, João Paulo Papa, Xin-She Yang
Feature selection for a given model can be transformed into an optimization task. The essential idea behind it is to find the most suitable subset of features according to some cri…
Fast Ensemble Learning Using Adversarially-Generated Restricted Boltzmann Machines
Gustavo H. de Rosa, Mateus Roder, João P. Papa
Machine Learning has been applied in a wide range of tasks throughout the last years, ranging from image classification to autonomous driving and natural language processing. Restr…