In today’s large and complex network scenario vulnerability scanners play a major role from security perspective by proactively identifying the known security problems or vulner...
We show how a preselection of hidden variables can be used to efficiently train generative models with binary hidden variables. The approach is based on Expectation Maximization (...
This work presents a new statistical approach to region merging where regions are modeled as arbitrary discrete distributions, directly estimated from the pixel values. Under this...
Dimensionality reduction is a statistical tool commonly used to map high-dimensional data into lower a dimensionality. The transformed data is typically more suitable for regressi...
Bill Kapralos, Nathan Mekuz, Agnieszka Kopinska, S...
We introduce a new technique that can reduce any
higher-order Markov random field with binary labels into
a first-order one that has the same minima as the original.
Moreover, w...