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Why so gloomy? A Bayesian explanation of human pessimism bias in the multi-armed bandit task
We find that the "pessimism bias" in the bandit task is well captured by the prior mean of DBM when fitted to human choices; but it is poorly captured by the prior mean of the Fixed Belief Model (FBM), an alternative Bayesian model that (correctly) assumes reward rates to be constants.
Deep Bayesian Bandits: Exploring in Online Personalized Recommendations
Recommender systems trained in a continuous learning fashion are plagued by the feedback loop problem, also known as algorithmic bias.
Should I send this notification? Optimizing push notifications decision making by modeling the future
In this work we focus on mobile push notifications, where the long term effects of recommender system decisions can be particularly strong.
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