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Cited by

• 2018Hedging the Drift: Learning to Optimize Under Non-Stationarity83 cited
• 2023Nearly Minimax-Optimal Regret for Linearly Parameterized Bandits76 cited
• 2018Learning Contextual Bandits in a Non-stationary Environment68 cited
• 2019A New Algorithm for Non-stationary Contextual Bandits: Efficient, Optimal, and Parameter-free62 cited
• 2020Sliding-Window Thompson Sampling for Non-Stationary Settings61 cited
• 2019Model selection for contextual bandits42 cited
• 2020Reinforcement Learning for Non-Stationary Markov Decision Processes: The Blessing of (More) Optimism40 cited
• 2023Nonstationary Reinforcement Learning: The Blessing of (More) Optimism34 cited