136 citations · 421 across the 32 of their papers we have counts for
12 papers · 1 filter
Protected Attributes Tell Us Who, Behavior Tells Us How: A Comparison of Demographic and Behavioral Oversampling for Fair Student Success Modeling
Jade Maï Cock, Muhammad Bilal, Richard Davis +2
Algorithms deployed in education can shape the learning experience and success of a student. It is therefore important to understand whether and how such algorithms might create in…
Do Not Trust a Model Because It is Confident: Uncovering and Characterizing Unknown Unknowns to Student Success Predictors in Online-Based Learning
Roberta Galici, Tanja Käser, Gianni Fenu +1
Student success models might be prone to develop weak spots, i.e., examples hard to accurately classify due to insufficient representation during model creation. This weakness is o…
Trusting the Explainers: Teacher Validation of Explainable Artificial Intelligence for Course Design
Vinitra Swamy, Sijia Du, Mirko Marras +1
Deep learning models for learning analytics have become increasingly popular over the last few years; however, these approaches are still not widely adopted in real-world settings,…
The More Secure, The Less Equally Usable: Gender and Ethnicity (Un)fairness of Deep Face Recognition along Security Thresholds
Andrea Atzori, Gianni Fenu, Mirko Marras
Face biometrics are playing a key role in making modern smart city applications more secure and usable. Commonly, the recognition threshold of a face recognition system is adjusted…
Reinforcement Recommendation Reasoning through Knowledge Graphs for Explanation Path Quality
Giacomo Balloccu, Ludovico Boratto, Gianni Fenu +1
Numerous Knowledge Graphs (KGs) are being created to make Recommender Systems (RSs) not only intelligent but also knowledgeable. Integrating a KG in the recommendation process allo…
Explaining Bias in Deep Face Recognition via Image Characteristics
Andrea Atzori, Gianni Fenu, Mirko Marras
In this paper, we propose a novel explanatory framework aimed to provide a better understanding of how face recognition models perform as the underlying data characteristics (prote…
Experts' View on Challenges and Needs for Fairness in Artificial Intelligence for Education
Gianni Fenu, Roberta Galici, Mirko Marras
In recent years, there has been a stimulating discussion on how artificial intelligence (AI) can support the science and engineering of intelligent educational applications. Many s…
Regulating Group Exposure for Item Providers in Recommendation
Mirko Marras, Ludovico Boratto, Guilherme Ramos +1
Engaging all content providers, including newcomers or minority demographic groups, is crucial for online platforms to keep growing and working. Hence, while building recommendatio…
Post Processing Recommender Systems with Knowledge Graphs for Recency, Popularity, and Diversity of Explanations
Giacomo Balloccu, Ludovico Boratto, Gianni Fenu +1
Existing explainable recommender systems have mainly modeled relationships between recommended and already experienced products, and shaped explanation types accordingly (e.g., mov…
Dictionary Attacks on Speaker Verification
Mirko Marras, Pawel Korus, Anubhav Jain +1
In this paper, we propose dictionary attacks against speaker verification - a novel attack vector that aims to match a large fraction of speaker population by chance. We introduce…
Robust Reputation Independence in Ranking Systems for Multiple Sensitive Attributes
Guilherme Ramos, Ludovico Boratto, Mirko Marras
Ranking systems have an unprecedented influence on how and what information people access, and their impact on our society is being analyzed from different perspectives, such as us…
Consumer Fairness in Recommender Systems: Contextualizing Definitions and Mitigations
Ludovico Boratto, Gianni Fenu, Mirko Marras +1
Enabling non-discrimination for end-users of recommender systems by introducing consumer fairness is a key problem, widely studied in both academia and industry. Current research h…