Transfer learning for piecewise-constant mean estimation: optimality, ℓ 1 and ℓ 0 penalization
分段常数均值估计的迁移学习：最优性与ℓ₁、ℓ₀惩罚
Summary We study transfer learning for estimating piecewise-constant signals when source data, which may be relevant but disparate, are available in addition to target data. We first investigate transfer learning estimators that respectively employ $ \ell_{1} $ and $ \ell_{0} $ penalties for unisource data scenarios and then generalize these estimators to accommodate multisources. To further reduce estimation errors, especially when some sources significantly differ from the…