566 citations · 1k across the 14 of their papers we have counts for
26 papers
Fast online ranking with fairness of exposure
Nicolas Usunier, Virginie Do, Elvis Dohmatob
As recommender systems become increasingly central for sorting and prioritizing the content available online, they have a growing impact on the opportunities or revenue of their it…
Fairness Indicators for Systematic Assessments of Visual Feature Extractors
Priya Goyal, Adriana Romero Soriano, Caner Hazirbas +2
Does everyone equally benefit from computer vision systems? Answers to this question become more and more important as computer vision systems are deployed at large scale, and can…
Two-sided fairness in rankings via Lorenz dominance
Virginie Do, Sam Corbett-Davies, Jamal Atif +1
We consider the problem of generating rankings that are fair towards both users and item producers in recommender systems. We address both usual recommendation (e.g., of music or m…
Hierarchical Skills for Efficient Exploration
Jonas Gehring, Gabriel Synnaeve, Andreas Krause +1
In reinforcement learning, pre-trained low-level skills have the potential to greatly facilitate exploration. However, prior knowledge of the downstream task is required to strike…
A Self-Supervised Auxiliary Loss for Deep RL in Partially Observable Settings
Eltayeb Ahmed, Luisa Zintgraf, Christian A. Schroeder de Witt +1
In this work we explore an auxiliary loss useful for reinforcement learning in environments where strong performing agents are required to be able to navigate a spatial environment…
Gradient Matching for Domain Generalization
Yuge Shi, Jeffrey Seely, Philip H. S. Torr +4
Machine learning systems typically assume that the distributions of training and test sets match closely. However, a critical requirement of such systems in the real world is their…