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stat.ML2024
Sparse Linear Regression when Noises and Covariates are Heavy-Tailed and Contaminated by Outliers
Takeyuki Sasai, Hironori Fujisawa
We investigate a problem estimating coefficients of linear regression under sparsity assumption when covariates and noises are sampled from heavy tailed distributions. Additionally…
stat.ML2022★ 1 cited
Robust and Sparse Estimation of Linear Regression Coefficients with Heavy-tailed Noises and Covariates
Takeyuki Sasai
Robust and sparse estimation of linear regression coefficients is investigated. The situation addressed by the present paper is that covariates and noises are sampled from heavy-ta…
stat.ML2020
Adversarial Robust Low Rank Matrix Estimation: Compressed Sensing and Matrix Completion
Takeyuki Sasai, Hironori Fujisawa
We consider robust low rank matrix estimation as a trace regression when outputs are contaminated by adversaries. The adversaries are allowed to add arbitrary values to arbitrary o…