Our problem of interest consists of minimizing a separable, convex and differentiable function over a convex set, defined by bounds on the variables and an explicit constraint des...
Abstract. Subspace mapping methods aim at projecting high-dimensional data into a subspace where a specific objective function is optimized. Such dimension reduction allows the re...
Axel J. Soto, Marc Strickert, Gustavo E. Vazquez, ...
This paper extends an adaptive discretization method, Spliton-Demand (SoD), to be capable of handling multidimensional continuous search spaces. The proposed extension is called m...
On machines with high-performance processors, the memory system continues to be a performance bottleneck. Compilers insert prefetch operations and reorder data accesses to improve...
Nathaniel McIntosh, Sandya Mannarswamy, Robert Hun...
This paper describes a continuous estimation of distribution algorithm (EDA) to solve decomposable, real-valued optimization problems quickly, accurately, and reliably. This is the...
Chang Wook Ahn, Rudrapatna S. Ramakrishna, David E...