We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
Abstract. We develop a practical, distributed algorithm to detect events, identify measurement errors, and infer missing readings in ecological applications of wireless sensor netw...
: This article describes the use of a service-oriented architecture to bridge the gap between different eLearning types and tools. The basic concept is a bi-directional distributio...
A major difficulty in building Bayesian network models is the size of conditional probability tables, which grow exponentially in the number of parents. One way of dealing with th...
With the rise of VR, the internet, and mobile technologies and the shifts in educational focus from teaching to learning and from solitary to collaborative work, it's easy (bu...