Suman K. Sen

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The Support Vector Machine (SVM) is a powerful tool for classification. We generalize SVM to work with data objects that are naturally understood to be lying on curved manifolds, and not in the usual d-dimensional Euclidean space. Such data arise from medial representations (m-reps) in medical images, Diffusion Tensor-MRI (DT-MRI), diffeomorphisms, etc.(More)
SUMAN KUMAR SEN: Classification on Manifolds (Under the direction of Dr. James S. Marron) This dissertation studies classification on smooth manifolds and the behavior of High Dimensional Low Sample Size (HDLSS) data as the dimension increases. In modern image analysis, statistical shape analysis plays an important role in understanding several diseases.(More)
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