9 citations · 13 across the 4 of their papers we have counts for
4 papers
FedFlex: Federated Learning for Diverse Netflix Recommendations
Sven Lankester, Gustavo de Carvalho Bertoli, Matias Vizcaino +2
The drive for personalization in recommender systems creates a tension between user privacy and the risk of "filter bubbles". Although federated learning offers a promising paradig…
Hierarchical Multi-Positive Contrastive Learning for Patent Image Retrieval
Kshitij Kavimandan, Angelos Nalmpantis, Emma Beauxis-Aussalet +1
Patent images are technical drawings that convey information about a patent's innovation. Patent image retrieval systems aim to search in vast collections and retrieve the most rel…
How Do Companies Manage the Environmental Sustainability of AI? An Interview Study About Green AI Efforts and Regulations
Ashmita Sampatsing, Sophie Vos, Emma Beauxis-Aussalet +1
With the ever-growing adoption of artificial intelligence (AI), AI-based software and its negative impact on the environment are no longer negligible, and studying and mitigating t…
Analysing and Organising Human Communications for AI Fairness-Related Decisions: Use Cases from the Public Sector
Mirthe Dankloff, Vanja Skoric, Giovanni Sileno +3
AI algorithms used in the public sector, e.g., for allocating social benefits or predicting fraud, often involve multiple public and private stakeholders at various phases of the a…