5 papers
Transfer Learning for Evolving Domains
Ricardo Ribeiro Pereira, Jacopo Bono, Hugo Ferreira +4
Transfer learning explores how to leverage knowledge from various tasks or domains (sources) to enhance predictive performance in related tasks or domains (targets). Typically, tra…
Rethinking XAI Evaluation: A Human-Centered Audit of Shapley Benchmarks in High-Stakes Settings
Inês Oliveira e Silva, Sérgio Jesus, Iker Perez +4
Shapley values are a cornerstone of explainable AI, yet their proliferation into competing formulations has created a fragmented landscape with little consensus on practical deploy…
Evaluating Transfer Learning Methods on Real-World Data Streams: A Case Study in Financial Fraud Detection
Ricardo Ribeiro Pereira, Jacopo Bono, Hugo Ferreira +3
When the available data for a target domain is limited, transfer learning (TL) methods can be used to develop models on related data-rich domains, before deploying them on the targ…
Fair-OBNC: Correcting Label Noise for Fairer Datasets
Inês Oliveira e Silva, Sérgio Jesus, Hugo Ferreira +4
Data used by automated decision-making systems, such as Machine Learning models, often reflects discriminatory behavior that occurred in the past. These biases in the training data…
RIFF: Inducing Rules for Fraud Detection from Decision Trees
João Lucas Martins, João Bravo, Ana Sofia Gomes +2
Financial fraud is the cause of multi-billion dollar losses annually. Traditionally, fraud detection systems rely on rules due to their transparency and interpretability, key featu…