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09/14/2023
FedFNN: Faster Training Convergence Through Update Predictions in Federated Recommender Systems
Federated Learning (FL) has emerged as a key approach for distributed ma...
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08/23/2023
Counterfactual Graph Augmentation for Consumer Unfairness Mitigation in Recommender Systems
In recommendation literature, explainability and fairness are becoming t...
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04/12/2023
GNNUERS: Fairness Explanation in GNNs for Recommendation via Counterfactual Reasoning
In recent years, personalization research has been delving into issues o...
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01/05/2023
Max-Min Diversification with Fairness Constraints: Exact and Approximation Algorithms
Diversity maximization aims to select a diverse and representative subse...
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07/30/2022
Streaming Algorithms for Diversity Maximization with Fairness Constraints
Diversity maximization is a fundamental problem with wide applications i...
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02/01/2022
Rewiring What-to-Watch-Next Recommendations to Reduce Radicalization Pathways
Recommender systems typically suggest to users content similar to what t...
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10/09/2020
Streaming Submodular Maximization with Fairness Constraints
We study the problem of extracting a small subset of representative item...
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06/04/2020
The relationship between human mobility and viral transmissibility during the COVID-19 epidemics in Italy
We describe in this report our studies to understand the relationship be...
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04/23/2020
