most citedResampling strategies for imbalanced regression: a survey and empirical analysis

52 citations · 55 across the 9 of their papers we have counts for

collaborators

9 papers

cs.LG2026

Instance Hardness-Based Relevance for Imbalanced Regression

Vitor M. Leitao, Juscimara G. Avelino, George D. C. Cavalcanti +1

Imbalanced regression problems arise when the target variable has an asymmetric distribution, resulting in underrepresented value ranges in the dataset. Traditional approaches for…

cs.SE2026

Multi-stage Dynamic Selection for Cross-Project Defect Prediction

Juscimara G. Avelino, Juscelino S. A. Junior, George D. C. Cavalcanti +1

Cross-Project Defect Prediction (CPDP) involves building models using data from external projects, called training projects, to predict modules from the target project. However, tr…

cs.LG2025

DRES: Fake news detection by dynamic representation and ensemble selection

Faramarz Farhangian, Leandro A. Ensina, George D. C. Cavalcanti +1

The rapid spread of information via social media has made text-based fake news detection critically important due to its societal impact. This paper presents a novel detection meth…

cs.LG2025

PIPES: A Meta-dataset of Machine Learning Pipelines

Cynthia Moreira Maia, Lucas B. V. de Amorim, George D. C. Cavalcanti +1

Solutions to the Algorithm Selection Problem (ASP) in machine learning face the challenge of high computational costs associated with evaluating various algorithms' performances on…

cs.CL2025

HSFN: Hierarchical Selection for Fake News Detection building Heterogeneous Ensemble

Sara B. Coutinho, Rafael M. O. Cruz, Francimaria R. S. Nascimento +1

Psychological biases, such as confirmation bias, make individuals particularly vulnerable to believing and spreading fake news on social media, leading to significant consequences…

cs.LG2025★ 52 cited

Resampling strategies for imbalanced regression: a survey and empirical analysis

Juscimara G. Avelino, George D. C. Cavalcanti, Rafael M. O. Cruz

Imbalanced problems can arise in different real-world situations, and to address this, certain strategies in the form of resampling or balancing algorithms are proposed. This issue…

cs.LG2025★ 2 cited

Imbalanced Regression Pipeline Recommendation

Juscimara G. Avelino, George D. C. Cavalcanti, Rafael M. O. Cruz

Imbalanced problems are prevalent in various real-world scenarios and are extensively explored in classification tasks. However, they also present challenges for regression tasks d…

cs.CL2025★ 1 cited

Multi-view autoencoders for Fake News Detection

Ingryd V. S. T. Pereira, George D. C. Cavalcanti, Rafael M. O. Cruz

Given the volume and speed at which fake news spreads across social media, automatic fake news detection has become a highly important task. However, this task presents several cha…

cs.CR2025

Imbalanced malware classification: an approach based on dynamic classifier selection

J. V. S. Souza, C. B. Vieira, G. D. C. Cavalcanti +1

In recent years, the rise of cyber threats has emphasized the need for robust malware detection systems, especially on mobile devices. Malware, which targets vulnerabilities in dev…