[Makoto Yamada] Nonlinear machine learning for scientific discovery

PRESTO Researcher

Makoto Yamada

Makoto Yamada

Kyoto University
Graduate School of Informatics
Associate Professor

Outline

In this project, we will develop a machine learning algorithm for scientific discovery. More specifically, we will develp a nonlinear feature selection algorithm for high-dimensional big data based on sparse modeling techniques. We plan to apply the proposed algorithms for a number of applications including biomarker detection and material discovery.

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