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Applied Machine Learning

This group is interested in computer algorithms which can “learn” a behavior in order to achieve a given task of interest, in contrast to algorithms with behavior constrained by handcrafted rules. Research is driven by real-world applications involving large amounts of data. Domains of interest include natural language processing, computer vision, and audio processing. A particular emphasis is placed on generic machinelearning tools which require minimum a priori knowledge of the data (such as deep-learning techniques), as well as on unsupervised learning techniques which can leverage inherent semantics from large-scale, structured data.

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