activity
20152023
most citedScaling associative classification for very large datasets

12 citations · 32 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2023

Explaining Speech Classification Models via Word-Level Audio Segments and Paralinguistic Features

Eliana Pastor, Alkis Koudounas, Giuseppe Attanasio +2

Recent advances in eXplainable AI (XAI) have provided new insights into how models for vision, language, and tabular data operate. However, few approaches exist for understanding s…

cs.CL2023★ 8 cited

ITALIC: An Italian Intent Classification Dataset

Alkis Koudounas, Moreno La Quatra, Lorenzo Vaiani +5

Recent large-scale Spoken Language Understanding datasets focus predominantly on English and do not account for language-specific phenomena such as particular phonemes or words in…

cs.CL2022★ 4 cited

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…

cs.LG2021★ 4 cited

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…

cs.LG2019★ 3 cited

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…

cs.LG2018★ 12 cited

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…

cs.NI2015★ 1 cited

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…