Junpei Komiyama

Junpei Komiyama

Assistant Professor at MBZUAI. Research: Machine Learning, Multi-armed Bandits, Monte Carlo Tree Search, Algorithmic Bias

Position-based Multiple-play Bandit Problem with Unknown Position Bias

Published in Advances in Neural Information Processing Systems (NIPS), 2017

This paper addresses position-based multiple-play bandit problems with unknown position bias. We provide theoretical analysis and practical algorithms for scenarios where the position of displayed items affects user engagement, with applications to recommendation systems and online advertising.

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Recommended citation: Komiyama, J., Honda, J., & Takeda, A. (2017). “Position-based Multiple-play Bandit Problem with Unknown Position Bias.” In Advances in Neural Information Processing Systems 30 (NIPS 2017), 5005-5015.

Recommended citation: Komiyama, J., Honda, J., & Takeda, A. (2017). "Position-based Multiple-play Bandit Problem with Unknown Position Bias." In Advances in Neural Information Processing Systems 30 (NIPS 2017), 5005-5015.
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