Junpei Komiyama

Junpei Komiyama

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

Statistical Emerging Pattern Mining with Multiple Testing Correction

Published in ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017

This paper develops statistical methods for emerging pattern mining with multiple testing correction. We provide rigorous statistical guarantees for pattern discovery, addressing the multiple testing problem that arises when searching for significant patterns in large datasets.

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Recommended citation: Komiyama, J., Ishihata, M., Arimura, H., Nishibayashi, T., & Minato, S. (2017). “Statistical Emerging Pattern Mining with Multiple Testing Correction.” In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2017), 897-906.

Recommended citation: Komiyama, J., Ishihata, M., Arimura, H., Nishibayashi, T., & Minato, S. (2017). "Statistical Emerging Pattern Mining with Multiple Testing Correction." In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2017), 897-906.
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