Change point detection algorithms have numerous applications in areas of medical condition monitoring, fault industrial processes, human activity analysis, climate change detection, and speech recognition. We consider the problem on compositional multivariate data (each sample is a probability mass function), which practically important sub-class general data. While change-point well studied un...

Visualization of 2D point clouds is one of the most basic yet one of the most important problems in many visual data analysis tasks. Point clouds arise in many contexts including scatter plot analysis, or the visualization of high-dimensional or geo-spatial data. Typical analysis tasks in point cloud data include assessing the overall structure and distribution of the data, assessing spatial re...

Data augmentation is an important technique to improve data efficiency and save labeling cost for 3D detection in point clouds. Yet, existing policies have so far been designed only utilize labeled data, which limits the diversity. In this paper, we recognize that pseudo are complementary, thus propose leverage unlabeled enrich training data. particular, design three novel pseudo-label based (P...