6 citations · 10 across the 7 of their papers we have counts for
Showing stat.MLShow all
2 papers · 1 filter
stat.ML2023
Weighted Tallying Bandits: Overcoming Intractability via Repeated Exposure Optimality
Dhruv Malik, Conor Igoe, Yuanzhi Li +1
In recommender system or crowdsourcing applications of online learning, a human's preferences or abilities are often a function of the algorithm's recent actions. Motivated by this…
stat.ML2022
Complete Policy Regret Bounds for Tallying Bandits
Dhruv Malik, Yuanzhi Li, Aarti Singh
Policy regret is a well established notion of measuring the performance of an online learning algorithm against an adaptive adversary. We study restrictions on the adversary that e…