Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA includes a collecti...
Albert Bifet, Geoff Holmes, Richard Kirkby, Bernha...
We study the problem of learning to rank images for image retrieval. For a noisy set of images indexed or tagged by the same keyword, we learn a ranking model from some training e...
Learning agents can improve performance cooperating with other agents, particularly learning agents forming a committee outperform individual agents. This "ensemble effect&qu...
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Pervasive computing environment and users’ demand for multimedia personalization precipitate a need for personalization tools to help people access desired multimedia content at ...