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In the given text, we discuss the application of a sparse coding algorithm. Additionally, we can explore the utilization of this efficient sparse coding algorithm in a novel machine learning framework known as "self-taught learning". In this framework, we are provided with a limited amount of labeled data for a supervised learning task. Furthermore, we have access to a large volume of unlabeled data that is unrelated to the supervised problem's labels and does not originate from the same distribution.