Semi-supervised clustering uses a small amount of supervised data to aid unsupervised learning. One typical approach specifies a limited number of must-link and cannotlink constra...
This paper presents a general framework for adapting any generative (model-based) clustering algorithm to provide balanced solutions, i.e., clusters of comparable sizes. Partition...
This research investigates the detection of student meta-cognitive planning processes in real-time using log tracing techniques. We use fine and coarse-grained data distillation, i...
Orlando Montalvo, Ryan Shaun Joazeiro de Baker, Mi...
The importance of learning distance functions is gradually being acknowledged by the machine learning community, and different techniques are suggested that can successfully learn ...
Abstract. The high dimensionality of the data generated by social networks has been a big challenge for researchers. In order to solve the problems associated with this phenomenon,...