3 citations · 5 across the 10 of their papers we have counts for
15 papers
Band Relevance Factor (BRF): a novel automatic frequency band selection method based on vibration analysis for rotating machinery
Lucas Costa Brito, Gian Antonio Susto, Jorge Nei Brito +1
The monitoring of rotating machinery has now become a fundamental activity in the industry, given the high criticality in production processes. Extracting useful information from r…
Fault Diagnosis using eXplainable AI: a Transfer Learning-based Approach for Rotating Machinery exploiting Augmented Synthetic Data
Lucas Costa Brito, Gian Antonio Susto, Jorge Nei Brito +1
Artificial Intelligence (AI) is one of the approaches that has been proposed to analyze the collected data (e.g., vibration signals) providing a diagnosis of the asset's operating…
On the Properties of Adversarially-Trained CNNs
Mattia Carletti, Matteo Terzi, Gian Antonio Susto
Adversarial Training has proved to be an effective training paradigm to enforce robustness against adversarial examples in modern neural network architectures. Despite many efforts…
Learning to Rank from Relevance Judgments Distributions
Alberto Purpura, Gianmaria Silvello, Gian Antonio Susto
Learning to Rank (LETOR) algorithms are usually trained on annotated corpora where a single relevance label is assigned to each available document-topic pair. Within the Cranfield…
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…