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2020 – today
- 2024
[c3]Danil Provodin, Maurits Clemens Kaptein, Mykola Pechenizkiy:
Efficient Exploration in Average-Reward Constrained Reinforcement Learning: Achieving Near-Optimal Regret With Posterior Sampling. ICML 2024- [c2]Danil Provodin
, Jérémie Joudioux, Eduard Duryev:
Bandits for Sponsored Search Auctions Under Unknown Valuation Model: Case Study in E-Commerce Advertising. ECML/PKDD (10) 2024: 263-279 - [i7]Danil Provodin, Maurits Kaptein, Mykola Pechenizkiy:
Efficient Exploration in Average-Reward Constrained Reinforcement Learning: Achieving Near-Optimal Regret With Posterior Sampling. CoRR abs/2405.19017 (2024) - [i6]Danil Provodin, Bram van den Akker, Christina Katsimerou, Maurits Kaptein, Mykola Pechenizkiy:
Rethinking Knowledge Transfer in Learning Using Privileged Information. CoRR abs/2408.14319 (2024) - 2023
- [i5]Danil Provodin, Jérémie Joudioux, Eduard Duryev:
Learning Optimal Bidding Strategy: Case Study in E-Commerce Advertising. CoRR abs/2304.00999 (2023) - [i4]Danil Provodin, Pratik Gajane, Mykola Pechenizkiy, Maurits Kaptein:
Provably Efficient Exploration in Constrained Reinforcement Learning: Posterior Sampling Is All You Need. CoRR abs/2309.15737 (2023) - 2022
- [c1]Danil Provodin, Pratik Gajane, Mykola Pechenizkiy, Maurits Kaptein:
The Impact of Batch Learning in Stochastic Linear Bandits. ICDM 2022: 1149-1154 - [i3]Danil Provodin, Pratik Gajane, Mykola Pechenizkiy, Maurits Kaptein:
The Impact of Batch Learning in Stochastic Linear Bandits. CoRR abs/2202.06657 (2022) - [i2]Danil Provodin, Pratik Gajane, Mykola Pechenizkiy, Maurits Kaptein:
An Empirical Evaluation of Posterior Sampling for Constrained Reinforcement Learning. CoRR abs/2209.03596 (2022) - 2021
- [i1]Danil Provodin, Pratik Gajane, Mykola Pechenizkiy, Maurits Kaptein:
The Impact of Batch Learning in Stochastic Bandits. CoRR abs/2111.02071 (2021)
Coauthor Index
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