We propose a visualization method based on a topic model for discrete data such as documents. Unlike conventional visualization methods based on pairwise distances such as multi-d...
This paper presents an LDA-style topic model that captures not only the low-dimensional structure of data, but also how the structure changes over time. Unlike other recent work t...
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
An adaptive semi-supervised ensemble method, ASSEMBLE, is proposed that constructs classification ensembles based on both labeled and unlabeled data. ASSEMBLE alternates between a...
This paper introduces bubbling menus, a new design for cascading drop-down menus. Bubbling menus combine the bubble cursor [10] with directional mouse-gesture techniques to facili...