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math.ST2025
An Easily Tunable Approach to Robust and Sparse High-Dimensional Linear Regression
Takeyuki Sasai, Hironori Fujisawa
Sparse linear regression methods such as Lasso require a tuning parameter that depends on the noise variance, which is typically unknown and difficult to estimate in practice. In t…
math.ST2023
Estimation of sparse linear regression coefficients under -subexponential covariates
Takeyuki Sasai
We tackle estimating sparse coefficients in a linear regression when the covariates are sampled from an -subexponential random vector. This vector belongs to a class of distribu…