Beurling LASSO generalizes the LASSO problem to finite Radon measures regularized via their total variation. Despite its theoretical appeal, this space is hard to parametrize, which poses an algorithmic challenge. We propose a formulation of continuous convolutional source separation with Beurling LASSO that avoids the explicit computation of the measures and instead employs the duality transform of the proximal mapping.

翻译：LASSO(LASSO)将LASSO(LASSO)问题概括为通过其总变异而规范的有限辐射量措施。 尽管它具有理论上的吸引力,但这一空间很难进行平衡,这构成了一种算法上的挑战。 我们建议与Beurling LASSO(Beurling LASSO)制定一种持续革命源分离的配方,以避免对措施进行明确的计算,而是使用准成像绘图的双重转换。