Adaptive Forward-Backward Greedy Algorithm for Learning Sparse Representations

Given a large number of basis functions that can be potentially more than the number of samples, we consider the problem of learning a sparse target function that can be expressed as a linear combination of a small number of these basis functions. We are interested in two closely related themes: <orderedlist continuation="restarts" numeration="bullet" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <listitem><para>feature selection, or identifying the basis functions with nonzero coefficients;</para></listitem></orderedlist>