Active learning methods seek to reduce the number of labeled examples needed to train an effective classifier, and have natural appeal in spam filtering applications where trustwo...
In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. Due to the tremendous (ex...
Abstract. Designs of micro electro-mechanical devices need to be robust against fluctuations in mass production. Computer experiments with tens of parameters are used to explore th...
The rapid evolution and ubiquitous use of mobile devices is an historical opportunity to improve experiential interactivity in education practices to support “deep” learning. ...
Andrew Litchfield, Ryszard Raban, Laurel Evelyn Dy...
This paper presents an improved software estimation model, which uses to estimate developing effort of e-Learning's contents. This model is called the e-Learning courseware E...