6 papers
Geometrical fairness in graph neural networks
Arturo Pérez-Peralta, Sandra BenÃtez-Peña, Blas Kolic +1
Graph-based learning methods have become increasingly prominent due to their strong performance across diverse applications. Among these, recent frameworks grounded in diffusion pr…
On the use of graph models to achieve individual and group fairness
Arturo Pérez-Peralta, Sandra BenÃtez-Peña, Rosa E. Lillo
Machine Learning algorithms are ubiquitous in key decision-making contexts such as justice, healthcare and finance, which has spawned a great demand for fairness in these procedure…
FairLangProc: A Python package for fairness in NLP
Arturo Pérez-Peralta, Sandra BenÃtez-Peña, Rosa E. Lillo
The rise in usage of Large Language Models to near ubiquitousness in recent years has risen societal concern about their applications in decision-making contexts, such as organizat…
Area-based epigraph and hypograph indices for functional outlier detection
Belen Pulido, Alba M. Franco-Pereira, Rosa E. Lillo +1
Detecting outliers in Functional Data Analysis is challenging because curves can stray from the majority in many different ways. The Modified Epigraph Index (MEI) and Modified Hypo…
The more the merrier: logical and multistage processors in credit scoring
Arturo Pérez-Peralta, Sandra BenÃtez-Peña, Rosa E. Lillo
Machine Learning algorithms are ubiquitous in key decision-making contexts such as organizational justice or healthcare, which has spawned a great demand for fairness in these proc…
Health Prognostics in Multi-sensor Systems Based on Multivariate Functional Data Analysis
Cevahir Yildirim, Alba M. Franco-Pereira, Rosa E. Lillo
Recent developments in big data analysis, machine learning, Industry 4.0, and IoT applications have enabled the monitoring and processing of multi-sensor data collected from system…