9 citations · 12 across the 14 of their papers we have counts for
3 papers · 1 filter
Scalable Multi-Objective Reinforcement Learning with Fairness Guarantees using Lorenz Dominance
Dimitris Michailidis, Willem Röpke, Diederik M. Roijers +2
Multi-Objective Reinforcement Learning (MORL) aims to learn a set of policies that optimize trade-offs between multiple, often conflicting objectives. MORL is computationally more…
Privacy-Aware Visual Language Models
Laurens Samson, Nimrod Barazani, Sennay Ghebreab +1
As Visual Language Models (VLMs) become increasingly embedded in everyday applications, ensuring they can recognise and appropriately handle privacy-sensitive content is thus essen…
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…