This paper describes a class ofprobabilistic approximation algorithms based on bucket elimination which o er adjustable levels of accuracy ande ciency. We analyzethe approximation...
We address the combinatorial optimization problem of finding the most influential nodes on a large-scale social network for two widely-used fundamental stochastic diffusion models...
—This paper studies the problem of allocating network capacity through periodic auctions. Motivated primarily by a service overlay architecture, we impose the following condition...
The problem of optimal node density maximizing the Neyman-Pearson detection error exponent subject to a constraint on average (per node) energy consumption is analyzed. The spatial...
The paper focuses on the study of solving the large-scale traveling salesman problem (TSP) based on neurodynamic programming. From this perspective, two methods, temporal differenc...
Jia Ma, Tao Yang, Zeng-Guang Hou, Min Tan, Derong ...