For unsupervised clustering in a network of spiking neurons we develop a temporal encoding of continuously valued data to obtain arbitrary clustering capacity and precision with a...
Abstract-- With the prevalence of multi-user environments, it has become an increasingly challenging task to precisely identify who is doing what on an enterprise network. Current ...
Qi Liao, Andrew Blaich, Aaron Striegel, Douglas Th...
The paper is an overview of a recently developed compilation data structure for graphical models, with specific application to constraint networks. The AND/OR Multi-Valued Decision...
Statistical machine learning techniques for data classification usually assume that all entities are i.i.d. (independent and identically distributed). However, real-world entities...
This paper describes the application of Real-Time Maude to the formal specification, simulation, and further formal analysis of the sophisticated state-of-the-art OGDC wireless se...