This paper describes how meta-level theories are used for analytic learning in M U L T I - T A C . M U L T I - T A C operationalizes generic heuristics for constraint-satisfaction...
Hashing based Approximate Nearest Neighbor (ANN) search has attracted much attention due to its fast query time and drastically reduced storage. However, most of the hashing metho...
Background: The application of machine learning to classification problems that depend only on positive examples is gaining attention in the computational biology community. We an...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
Most courses on Discrete Mathematics are designed to emphasize problem solving, in general. When the goal is to cover the content, the learning and understanding takes a second pl...
— In this paper, we study a qualitative property of a class of competitive learning (CL) models, which is called the multiplicatively biased competitive learning (MBCL) model, na...