4 citations · 12 across the 4 of their papers we have counts for
5 papers
Entropy-based Attention Regularization Frees Unintended Bias Mitigation from Lists
Giuseppe Attanasio, Debora Nozza, Dirk Hovy +1
Natural Language Processing (NLP) models risk overfitting to specific terms in the training data, thereby reducing their performance, fairness, and generalizability. E.g., neural h…
Identifying Biased Subgroups in Ranking and Classification
Eliana Pastor, Luca de Alfaro, Elena Baralis
When analyzing the behavior of machine learning algorithms, it is important to identify specific data subgroups for which the considered algorithm shows different performance with…
Automating concept-drift detection by self-evaluating predictive model degradation
Tania Cerquitelli, Stefano Proto, Francesco Ventura +2
A key aspect of automating predictive machine learning entails the capability of properly triggering the update of the trained model. To this aim, suitable automatic solutions to s…
Scaling associative classification for very large datasets
Luca Venturini, Elena Baralis, Paolo Garza
Supervised learning algorithms are nowadays successfully scaling up to datasets that are very large in volume, leveraging the potential of in-memory cluster-computing Big Data fram…
YouLighter: An Unsupervised Methodology to Unveil YouTube CDN Changes
Danilo Giordano, Stefano Traverso, Luigi Grimaudo +4
YouTube relies on a massively distributed Content Delivery Network (CDN) to stream the billions of videos in its catalogue. Unfortunately, very little information about the design…