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Found 7 papers, 1 papers with code
Auditing health-related recommendations in social media: A Case Study of Abortion on YouTube
Recommendation algorithms (RS) used by social media, like YouTube, significantly shape our information consumption across various domains, especially in healthcare.
FEBR: Expert-Based Recommendation Framework for beneficial and personalized content
The framework exploits the demonstrated trajectories of an expert (assumed to be reliable) in a recommendation evaluation environment, to recover an unknown utility function.
Tournesol: A quest for a large, secure and trustworthy database of reliable human judgments
We outline the structure of the Tournesol database, the key features of the Tournesol platform and the main hurdles that must be overcome to make it a successful project.
Removing Algorithmic Discrimination (With Minimal Individual Error)
We first solve the problem analytically in the case of two populations, with a uniform bonus-malus on the zones where each population is a majority.
Virtuously Safe Reinforcement Learning
We show that when a third party, the adversary, steps into the two-party setting (agent and operator) of safely interruptible reinforcement learning, a trade-off has to be made between the probability of following the optimal policy in the limit, and the probability of escaping a dangerous situation created by the adversary.
Learning to Gather without Communication
A standard belief on emerging collective behavior is that it emerges from simple individual rules.
Dynamic Safe Interruptibility for Decentralized Multi-Agent Reinforcement Learning
We give realistic sufficient conditions on the learning algorithm to enable dynamic safe interruptibility in the case of joint action learners, yet show that these conditions are not sufficient for independent learners.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
