14 citations · 41 across the 37 of their papers we have counts for
8 papers · 1 filter
AcME -- Accelerated Model-agnostic Explanations: Fast Whitening of the Machine-Learning Black Box
David Dandolo, Chiara Masiero, Mattia Carletti +2
In the context of human-in-the-loop Machine Learning applications, like Decision Support Systems, interpretability approaches should provide actionable insights without making the…
Improving Robustness with Image Filtering
Matteo Terzi, Mattia Carletti, Gian Antonio Susto
Adversarial robustness is one of the most challenging problems in Deep Learning and Computer Vision research. All the state-of-the-art techniques require a time-consuming procedure…
TiWS-iForest: Isolation Forest in Weakly Supervised and Tiny ML scenarios
Tommaso Barbariol, Gian Antonio Susto
Unsupervised anomaly detection tackles the problem of finding anomalies inside datasets without the labels availability; since data tagging is typically hard or expensive to obtain…
Incentives for Item Duplication under Fair Ranking Policies
Giorgio Maria Di Nunzio, Alessandro Fabris, Gianmaria Silvello +1
Ranking is a fundamental operation in information access systems, to filter information and direct user attention towards items deemed most relevant to them. Due to position bias,…
Algorithmic Audit of Italian Car Insurance: Evidence of Unfairness in Access and Pricing
Alessandro Fabris, Alan Mishler, Stefano Gottardi +4
We conduct an audit of pricing algorithms employed by companies in the Italian car insurance industry, primarily by gathering quotes through a popular comparison website. While ack…
Lazy FSCA for Unsupervised Variable Selection
Federico Zocco, Marco Maggipinto, Gian Antonio Susto +1
Various unsupervised greedy selection methods have been proposed as computationally tractable approximations to the NP-hard subset selection problem. These methods rely on sequenti…
An Explainable Artificial Intelligence Approach for Unsupervised Fault Detection and Diagnosis in Rotating Machinery
Lucas Costa Brito, Gian Antonio Susto, Jorge Nei Brito +1
The monitoring of rotating machinery is an essential task in today's production processes. Currently, several machine learning and deep learning-based modules have achieved excelle…
Neural Feature Selection for Learning to Rank
Alberto Purpura, Karolina Buchner, Gianmaria Silvello +1
LEarning TO Rank (LETOR) is a research area in the field of Information Retrieval (IR) where machine learning models are employed to rank a set of items. In the past few years, neu…