This thesis demonstrates techniques that provide faster and more
accurate solutions to a variety of problems in machine learning and
signal processing. The author proposes a "greedy" algorithm,
deriving sparse solutions with guarantees of optimality. The use of
this algorithm removes many of the inaccuracies that occurred with
the use of previous models.
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