We present a manifold learning approach to dimensionality
reduction that explicitly models the manifold as a mapping
from low to high dimensional space. The manifold is
represen...
Data cube has been playing an essential role in fast OLAP (online analytical processing) in many multi-dimensional data warehouses. However, there exist data sets in applications ...
Identifying information-rich subsets in high-dimensional spaces and representing them as order revealing patterns (or trends) is an important and challenging research problem in m...
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
Many authors in the field of 3D human computer interaction have described the advantages of 3D user interfaces: Intuitive metaphors from daily life, immersive workspaces, virtual ...