معرفی
Ikko Yamane is an Assistant Professor in the Computer Science Department at ENSAI, with a permanent membership at the Centre de Recherche en Economie et Statistique (CREST). His research focuses on machine learning, particularly in weakly supervised learning, domain adaptation, and multitask learning frameworks.
- PhD in Computer Science (2019) from University of Tokyo
- M.Eng and B.Sc from Tokyo Institute of Technology
Research interests include uplift modeling and multitask learning algorithms, evident from his open-source Python library development for causal inference tasks. His work bridges theoretical machine learning with practical applications in web marketing data analysis from his Yahoo! JAPAN internship.
Key research trends appear in
- Multitask Principal Component Analysis (2016)
- Uplift modeling
- Regularization techniques
He maintains strong academic ties with institutions including ENSAI, CREST, and the Sugiyama-Yokoya-Ishida Lab at University of Tokyo.
Ikko Yamane در سایتهای دیگر
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