Title: Expanding the Potential for Utilizing Tabular Data with Generative Models
Speaker: Hiroto Seki (Assistant Professor, Department of Applied Information Engineering, College of Science and Technology, Nihon University)
Abstract: Tabular data, such as medical records, POS data, customer records, and educational performance data, is utilized in diverse societal contexts. However, much of this data contains privacy information, imposing constraints on its use and sharing. Generative models, a prominent AI technology gaining attention in recent years, enable the creation of new data while preserving the characteristics of the original data. They are anticipated as a means to overcome this challenge. This presentation will provide an overview of methodologies for data synthesis using generative models applied to tabular data and explore potential applications in research and industry.
- Date
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24th October, 2025（Fri,）18:00～20:00
- Venue
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Held online
- Organizer
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Co-organizer (HRAM The Japan Society for Industrial and Applied Mathematics, D-DRIVE National Network)
- Participation Fee
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Free（Advance registration required）
https://www-mmds.sigmath.es.osaka-u.ac.jp/structure/activity/ai_data.php?id=101
- web
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https://www-mmds.sigmath.es.osaka-u.ac.jp/structure/activity/ai_data.php?id=101
- Contact
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Takashi Suzuki
suzuki@sigmath.es.osaka-u.ac.jp