Negative selection algorithms are immune-inspired classifiers that are trained on negative examples only. Classification is performed by generating detectors that match none of ...
Abstract. In recent years, there has been a growing interest in addressing dynamic optimization problems (DOPs) using evolutionary algorithms (EAs). Several approaches have been de...
Adapting to the network is the key to achieving high performance for communication-intensive applications, including scientific computing, data intensive computing, and multicast...
We present a novel approach to ray tracing execution on commodity graphics hardware using CUDA. We decompose
a standard ray tracing algorithm into several data-parallel stages tha...
Abstract--In this paper, we present an efficient graph-based evolutionary optimization technique called evolutionary graph generation (EGG) and the proposed approach is applied to ...