Distributed learning is a problem of fundamental interest in machine learning and cognitive science. In this paper, we present asynchronous distributed learning algorithms for two...
GPGPUs have recently emerged as powerful vehicles for generalpurpose high-performance computing. Although a new Compute Unified Device Architecture (CUDA) programming model from N...
The way conventional Ethernet is used today differs in two aspects from how dedicated system area networks are used. Firstly, dedicated system area networks are lossless and only d...
Two standard schemes for learning in classifier systems have been proposed in the literature: the bucket brigade algorithm (BBA) and the profit sharing plan (PSP). The BBA is a lo...
A synthetic noise function is a key component of most computer graphics rendering systems. This pseudo-random noise function is used to create a wide variety of natural looking te...