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01/03/2023
Heterogeneous Domain Adaptation and Equipment Matching: DANN-based Alignment with Cyclic Supervision (DBACS)
Process monitoring and control are essential in modern industries for en...
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12/30/2022
Time series Forecasting to detect anomalous behaviours in Multiphase Flow Meters
An Anomaly Detection (AD) System for Self-diagnosis has been developed f...
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12/21/2022
Continual Learning Approaches for Anomaly Detection
Anomaly Detection is a relevant problem that arises in numerous real-wor...
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12/04/2022
Band Relevance Factor (BRF): a novel automatic frequency band selection method based on vibration analysis for rotating machinery
The monitoring of rotating machinery has now become a fundamental activi...
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10/06/2022
Fault Diagnosis using eXplainable AI: a Transfer Learning-based Approach for Rotating Machinery exploiting Augmented Synthetic Data
Artificial Intelligence (AI) is one of the approaches that has been prop...
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08/08/2022
A Multi-label Continual Learning Framework to Scale Deep Learning Approaches for Packaging Equipment Monitoring
Continual Learning aims to learn from a stream of tasks, being able to r...
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07/08/2022
Active Learning-based Isolation Forest (ALIF): Enhancing Anomaly Detection in Decision Support Systems
The detection of anomalous behaviours is an emerging need in many applic...
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03/17/2022
On the Properties of Adversarially-Trained CNNs
Adversarial Training has proved to be an effective training paradigm to ...
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02/13/2022
Learning to Rank from Relevance Judgments Distributions
Learning to Rank (LETOR) algorithms are usually trained on annotated cor...
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02/03/2022
Algorithmic Fairness Datasets: the Story so Far
Data-driven algorithms are being studied and deployed in diverse domains...
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12/23/2021
AcME – Accelerated Model-agnostic Explanations: Fast Whitening of the Machine-Learning Black Box
In the context of human-in-the-loop Machine Learning applications, like ...
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12/21/2021
Improving Robustness with Image Filtering
Adversarial robustness is one of the most challenging problems in Deep L...
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11/30/2021
TiWS-iForest: Isolation Forest in Weakly Supervised and Tiny ML scenarios
Unsupervised anomaly detection tackles the problem of finding anomalies ...
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10/29/2021
Incentives for Item Duplication under Fair Ranking Policies
Ranking is a fundamental operation in information access systems, to fil...
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05/21/2021
Algorithmic Audit of Italian Car Insurance: Evidence of Unfairness in Access and Pricing
We conduct an audit of pricing algorithms employed by companies in the I...
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03/03/2021
Greedy Search Algorithms for Unsupervised Variable Selection: A Comparative Study
Dimensionality reduction is a important step in the development of scala...
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02/23/2021
An Explainable Artificial Intelligence Approach for Unsupervised Fault Detection and Diagnosis in Rotating Machinery
The monitoring of rotating machinery is an essential task in today's pro...
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02/22/2021
Neural Feature Selection for Learning to Rank
LEarning TO Rank (LETOR) is a research area in the field of Information ...
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09/02/2020
Gender Stereotype Reinforcement: Measuring the Gender Bias Conveyed by Ranking Algorithms
Search Engines (SE) have been shown to perpetuate well-known gender ster...
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08/20/2020
β-Variational Classifiers Under Attack
Deep Neural networks have gained lots of attention in recent years thank...
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08/03/2020
IntroVAC: Introspective Variational Classifiers for Learning Interpretable Latent Subspaces
Learning useful representations of complex data has been the subject of ...
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08/03/2020
Proximal Deterministic Policy Gradient
This paper introduces two simple techniques to improve off-policy Reinfo...
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07/22/2020
Adversarial Training Reduces Information and Improves Transferability
Recent results show that features of adversarially trained networks for ...
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07/21/2020
Interpretable Anomaly Detection with DIFFI: Depth-based Feature Importance for the Isolation Forest
Anomaly Detection is one of the most important tasks in unsupervised lea...
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10/08/2019
Directional Adversarial Training for Cost Sensitive Deep Learning Classification Applications
In many real-world applications of Machine Learning it is of paramount i...
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03/11/2019
