14 citations · 16 across the 4 of their papers we have counts for
5 papers
What Moved the Alarm Score? Causal Attribution with Exact Computation and Scarce-Incident Estimation
Masaaki Takada, Ryusei Shingaki
Alarms in industrial systems and scientific instruments often demand immediate diagnosis despite scarce incident data. To guide intervention, an explanation must trace how changes…
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,…
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…
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…
Independently Interpretable Lasso: A New Regularizer for Sparse Regression with Uncorrelated Variables
Masaaki Takada, Taiji Suzuki, Hironori Fujisawa
Sparse regularization such as regularization is a quite powerful and widely used strategy for high dimensional learning problems. The effectiveness of sparse regularizatio…