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Found 6 papers, 1 papers with code
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.
Learning to Rank For Push Notifications Using Pairwise Expected Regret
Listwise ranking losses have been widely studied in recommender systems.
Waiting but not Aging: Optimizing Information Freshness Under the Pull Model
Interestingly, we find that under this new Pull model, replication schemes capture a novel tradeoff between different values of the AoI across the servers (due to the random updating processes) and different response times across the servers, which can be exploited to minimize the expected AoI at the user's side.
Adaptive Exploration-Exploitation Tradeoff for Opportunistic Bandits
When the load/price is low, so is the cost/regret of pulling a suboptimal arm (e. g., trying a suboptimal network configuration).
Double Thompson Sampling for Dueling Bandits
This simple algorithm applies to general Copeland dueling bandits, including Condorcet dueling bandits as its special case.
Algorithms with Logarithmic or Sublinear Regret for Constrained Contextual Bandits
To the best of our knowledge, this is the first work that shows how to achieve logarithmic regret in constrained contextual bandits.
