Padhraic Smyth

TL;DR: The authors investigate a class of generative statistical topic models for multi-label documents that associate individual word tokens with different labels and investigate the advantages of this approach relative to discriminative models, particularly for classification problems involving large numbers of relatively rare labels.

TL;DR: The problems of temporal link prediction and node ranking are looked at, and new methods that illustrate opportunities for data mining and machine learning techniques in this context are described.

TL;DR: The UCI KDD Archive is described, which is a new online archive of large and complex data sets that encompasses a wide variety of data types, analysis tasks, and application areas and draws parallels with the development of the UCI Machine Learning Repository.

TL;DR: Data mining is on the interface of Computer Science andStatistics, utilizing advances in both disciplines to make progress in extracting information from large databases, and opportunities where close cooperation between the statistical and computational communities might reasonably provide synergy for further progress in data analysis are identified.

TL;DR: It is speculated that in humans the circadian clock imposes regulation of epidermal cell proliferation so that skin is at a particularly vulnerable stage during times of maximum UV exposure, thus contributing to the high incidence of human skin cancers.