Real-world data is known to be imperfect, suffering from various forms of defects such as sensor variability, estimation errors, uncertainty, human errors in data entry, and gaps ...
Feature selection has proven to be a valuable technique in supervised learning for improving predictive accuracy while reducing the number of attributes considered in a task. We i...
The paper focuses on the cognitive contribution of visual experiences to learning in a higher education setting. Specifically, it examines whether the use of students' imagin...
In this paper, we present an architecture for software agents that enables them to learn vocabulary through the observation of each other bodies and actions. Besides sensors, effe...
This paper has no novel learning or statistics: it is concerned with making a wide class of preexisting statistics and learning algorithms computationally tractable when faced wit...