An approach to mining repositories of web-based user documentation for patterns of evolutionary change in the context of internationalization and localization is presented. Localized web documents that are frequently co-changed (i.e., an evolutionary dependency) during the natural language translation process are uncovered to support the future evolution of the system. A sequential-pattern mini...

We study the problem of structured output learning from a regression perspective. We first provide a general formulation of the kernel dependency estimation (KDE) approach to this problem using operator-valued kernels. Our formulation overcomes the two main limitations of the original KDE approach, namely the decoupling between outputs in the image space and the inability to use a joint feature...

In classification, feature selection is an important pre-processing step to simplify the dataset and improve the data representation quality, which makes classifiers become better, easier to train, and understand. Because of an ability to analyse non-linear interactions between features, mutual information has been widely applied to feature selection. Along with counting approaches, a tradition...

Quantifying animals' home ranges is a key problem in ecology and has important conservation and wildlife management applications. Kernel density estimation (KDE) is a workhorse technique for range delineation problems that is both statistically efficient and nonparametric. KDE assumes that the data are independent and identically distributed (IID). However, animal tracking data, which are routi...

Efficient delineation of conservation areas is a great challenge in maintaining biodiversity. Kernel density estimators (KDEs) are a powerful tool in this perspective, but they have not been applied at the population level on patch-distributed organisms. This would be particularly worthy for species that need broad habitats beyond those where they can be sampled; such as terrestrial lands for p...

We report that the perception of three-dimensional structure from monocular two-dimensional images changing over time--the kinetic depth effect (KDE)--can evoke binocular eye movements consistent with a three-dimensional percept. We used a monocular KDE stimulus that induced a vivid perception of a rigid three-dimensional sphere rotating in space. The gaze directions of both eyes were measured ...

IGH gene rearrangement and IGK-Kde gene deletion can be used as molecular markers for the assessment of B lineage acute lymphoblastic leukemia (B-ALL). Minimal residual disease detected based on those markers is currently the most reliable prognosis factor in B-ALL. The aim of this study was to use clonal IGH/IGK-Kde gene rearrangements to confirm B-ALL diagnosis and to evaluate the treatment o...

Insufficiency of labeled training data is a major obstacle for automatic video annotation. Semi-supervised learning is an effective approach to this problem by leveraging a large amount of unlabeled data. However, existing semi-supervised learning algorithms have not demonstrated promising results in largescale video annotation due to several difficulties, such as large variation of video conte...