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The study and use of sparse representations in data-rich applications has garnered signicant attention in the signal processing, statistics, and machine learning communities. In the present work we describe a novel sensing procedure called Distilled Sensing (DS), which is a sequential and adaptive a ...

Traditional approaches to machine learning and statistical inference are passive, in the sense that all data are collected prior to analysis in a non-adaptive fashion. One can envision, however more active strategies in which information gleaned from previously collected data is used to guide the se ...