We address the problem of efficiently discovering the influential nodes in a social network under the susceptible/infected/susceptible (SIS) model, a diffusion model where nodes ar...
This paper describes a program, called NEWTON, that finds approximate symbolic solutions to parameterized equations in one variable. N E W T O N derives an initial approximation b...
The number of slices for error resilient video coding is jointly optimized with 802.11a-like media access control and the physical layers with automatic repeat request and rate com...
Reinforcement learning algorithms that employ neural networks as function approximators have proven to be powerful tools for solving optimal control problems. However, their traini...
This paper introduces a new approach to the problem of quantitative reconstruction of an object from few radiographic views. A mixed variable programming problem is formulated in ...
Mark A. Abramson, Thomas J. Asaki, J. E. Dennis, K...