|Component Analysis for Data Analysis
Component analysis (CA) is a set of techniques to decompose a signal (e.g. audio, video) into interesting components useful for classification, clustering, modeling or visualization. This project extends traditional CA techniques and unifies them, providing a cleaner theoretical framework for its analysis.
|Learning Kernel Expansions for Image Classification
Learning non-linear representations of a signal in order to improve classification performance.
|The Robotics Institute is part of the School of Computer Science, Carnegie Mellon University.|
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