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11/01/2020
Support Vector Machines and Radon's Theorem
A support vector machine (SVM) is an algorithm which finds a hyperplane ...
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06/27/2019
More chemical detection through less sampling: amplifying chemical signals in hyperspectral data cubes through compressive sensing
Compressive sensing (CS) is a method of sampling which permits some clas...
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06/20/2019
A data-driven approach to sampling matrix selection for compressive sensing
Sampling is a fundamental aspect of any implementation of compressive se...
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01/29/2019
Rare geometries: revealing rare categories via dimension-driven statistics
In many situations, the classes of data points of primary interest also ...
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10/27/2018
Monitoring the shape of weather, soundscapes, and dynamical systems: a new statistic for dimension-driven data analysis on large data sets
Dimensionality-reduction methods are a fundamental tool in the analysis ...
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08/05/2018
Too many secants: a hierarchical approach to secant-based dimensionality reduction on large data sets
A fundamental question in many data analysis settings is the problem of ...
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07/10/2018
A GPU-Oriented Algorithm Design for Secant-Based Dimensionality Reduction
Dimensionality-reduction techniques are a fundamental tool for extractin...
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07/03/2018
