Regret minimization has proven to be a very powerful tool in both computational learning theory and online algorithms. Regret minimization algorithms can guarantee, for a single de...
Learning elementary programming can be enhanced by introducing the notion of variable roles to students. This paper presents a web-based automatic role detection service that can ...
This paper proposes a very general max-margin learning framework for distance-based clustering. To this end, it formulates clustering as a high order energy minimization problem w...
The purpose of this paper is to describe in detail the current development status of the innovative Environment for Learning to Program (ELP) which provides an interactive web-bas...
Multiple-instance problems arise from the situations where training class labels are attached to sets of samples (named bags), instead of individual samples within each bag (called...