Compressive sensing (CS) exploits the sparsity present in many common signals to reduce the number of measurements needed for digital acquisition. With this reduction would come, ...
Mark A. Davenport, Jason N. Laska, John R. Treichl...
: Locality Sensitive Hash functions are invaluable tools for approximate near neighbor problems in high dimensional spaces. In this work, we are focused on LSH schemes where the si...
The proliferation of network data in various application domains has raised privacy concerns for the individuals involved. Recent studies show that simply removing the identities ...
As the use of the World Wide Web becomes more pervasive within our society, businesses and institutions are required to migrate a wide range of services to the web. Difficulties a...
Janet Lavery, Cornelia Boldyreff, Bin Ling, Colin ...
Bayesian graphical models are commonly used to build student models from data. A number of standard algorithms are available to train Bayesian models from student skills assessment...
Michel C. Desmarais, Alejandro Villarreal, Michel ...