Abstract— Creating exercises for learners requires significant time. This is one reason, beside difficulties of discussing individualized tasks in a classroom setting, why often ...
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Abstract. We discuss the design of an agent for coaching collaborative learning in a distance learning context. The learning domain is entity-relationship modeling, a domain in whi...
Pair programmers need a "warmup phase" before the pair can work at full speed. The length of the learning interval varies, depending on how experienced the developers are...
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...