6 citations · 7 across the 5 of their papers we have counts for
6 papers · 1 filter
A Survey on Semi-Supervised Learning for Delayed Partially Labelled Data Streams
Heitor Murilo Gomes, Maciej Grzenda, Rodrigo Mello +3
Unlabelled data appear in many domains and are particularly relevant to streaming applications, where even though data is abundant, labelled data is rare. To address the learning p…
Explainable Adversarial Attacks in Deep Neural Networks Using Activation Profiles
Gabriel D. Cantareira, Rodrigo F. Mello, Fernando V. Paulovich
As neural networks become the tool of choice to solve an increasing variety of problems in our society, adversarial attacks become critical. The possibility of generating data inst…
Ensuring Learning Guarantees on Concept Drift Detection with Statistical Learning Theory
Lucas Pagliosa, Rodrigo Mello
Concept Drift (CD) detection intends to continuously identify changes in data stream behaviors, supporting researchers in the study and modeling of real-world phenomena. Motivated…
Coarse-Refinement Dilemma: On Generalization Bounds for Data Clustering
Yule Vaz, Rodrigo Fernandes de Mello, Carlos Henrique Grossi
The Data Clustering (DC) problem is of central importance for the area of Machine Learning (ML), given its usefulness to represent data structural similarities from input spaces. D…
Computing the Shattering Coefficient of Supervised Learning Algorithms
Rodrigo Fernandes de Mello, Moacir Antonelli Ponti, Carlos Henrique Grossi Ferreira
The Statistical Learning Theory (SLT) provides the theoretical guarantees for supervised machine learning based on the Empirical Risk Minimization Principle (ERMP). Such principle…
Providing theoretical learning guarantees to Deep Learning Networks
Rodrigo Fernandes de Mello, Martha Dais Ferreira, Moacir Antonelli Ponti
Deep Learning (DL) is one of the most common subjects when Machine Learning and Data Science approaches are considered. There are clearly two movements related to DL: the first agg…