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stat.ML2023
Adaptive Lasso, Transfer Lasso, and Beyond: An Asymptotic Perspective
Masaaki Takada, Hironori Fujisawa
This paper presents a comprehensive exploration of the theoretical properties inherent in the Adaptive Lasso and the Transfer Lasso. The Adaptive Lasso, a well-established method,…
stat.ML2020★ 2 cited
Transfer Learning via Regularization
Masaaki Takada, Hironori Fujisawa
Machine learning algorithms typically require abundant data under a stationary environment. However, environments are nonstationary in many real-world applications. Critical issues…
stat.ML2018
HMLasso: Lasso with High Missing Rate
Masaaki Takada, Hironori Fujisawa, Takeichiro Nishikawa
Sparse regression such as the Lasso has achieved great success in handling high-dimensional data. However, one of the biggest practical problems is that high-dimensional data often…