The problem of transfer learning, where information gained in one learning task is used to improve performance in another related task, is an important new area of research. While...
Recently the academic communities have paid more attention to the queries and mining on uncertain data. In the tasks such as clustering or nearest-neighbor queries, expected distan...
In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. Due to the tremendous (ex...
Covariate shift is a situation in supervised learning where training and test inputs follow different distributions even though the functional relation remains unchanged. A common...
Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen...
In examining software maintenance processes for improvement opportunities, an obvious choice is information flow. Obtaining accurate, up-to-date, and useful information about a sy...