The Impact of Batch Learning in Stochastic Bandits. - Danil Provodin; Pratik Gajane; Mykola Pechenizkiy; Maurits Kaptein (CoRR, 2021)

The Impact of Batch Learning in Stochastic Linear Bandits. - Danil Provodin; Pratik Gajane; Mykola Pechenizkiy; Maurits Kaptein (ICDM, 2022)

An Empirical Evaluation of Posterior Sampling for Constrained Reinforcement Learning. - Danil Provodin; Pratik Gajane; Mykola Pechenizkiy; Maurits Kaptein (CoRR, 2022)

Learning Optimal Bidding Strategy: Case Study in E-Commerce Advertising. - Danil Provodin; Jérémie Joudioux; Eduard Duryev (CoRR, 2023)

Provably Efficient Exploration in Constrained Reinforcement Learning: Posterior Sampling Is All You Need. - Danil Provodin; Pratik Gajane; Mykola Pechenizkiy; Maurits Kaptein (CoRR, 2023)

Efficient Exploration in Average-Reward Constrained Reinforcement Learning: Achieving Near-Optimal Regret With Posterior Sampling. - Danil Provodin; Maurits Clemens Kaptein; Mykola Pechenizkiy (ICML, 2024)

Bandits for Sponsored Search Auctions Under Unknown Valuation Model: Case Study in E-Commerce Advertising. - Danil Provodin; Jérémie Joudioux; Eduard Duryev (ECML/PKDD (10), 2024)

Rethinking Knowledge Transfer in Learning Using Privileged Information. - Danil Provodin; Bram van den Akker; Christina Katsimerou; Maurits Clemens Kaptein; Mykola Pechenizkiy (Trans. Mach. Learn. Res., 2025)