Graph partitioning algorithms play a central role in data analysis and machine learning. Most useful graph partitioning criteria correspond to optimizing a ratio between the cut a...
—Approximating ideal program outputs is a common technique for solving computationally difficult problems, for adhering to processing or timing constraints, and for performance ...
Jason Ansel, Yee Lok Wong, Cy P. Chan, Marek Olsze...
In practical applications, Wireless Sensor Networks generate massive data streams with the dual attributes in geography and optimization domain. Energy source of sensor nodes in W...
Switched dynamical systems have shown great utility in modeling a variety of systems. Unfortunately, the determination of a numerical solution for the optimal control of such syste...
The Markov chain approximation method is an effective and widely used approach for computing optimal values and controls for stochastic systems. It was extended to nonlinear (and p...