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Found 3 papers, 2 papers with code
MultiScale Contextual Bandits for Long Term Objectives
To overcome this disconnect, we introduce the framework of MultiScale Policy Learning to contextually reconcile that AI systems need to act and optimize feedback at multiple interdependent timescales.
Fairness in Ranking under Disparate Uncertainty
While ranking can make human evaluation more effective by focusing attention on the most promising options, we argue that it can introduce unfairness if the uncertainty of the underlying relevance model differs between groups of options.
Semi-Parametric Inducing Point Networks and Neural Processes
We introduce semi-parametric inducing point networks (SPIN), a general-purpose architecture that can query the training set at inference time in a compute-efficient manner.
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