: Hierarchical graphs are graphs with layering structures; clustered graphs are graphs with recursive clustering structures. Both have applications in VLSI design, CASE tools, soft...
The detection of correlations between different features in high dimensional data sets is a very important data mining task. These correlations can be arbitrarily complex: One or...
We present a Fortran program to compute the distribution of dipole moments of free particles for use in analyzing molecular beams experiments that measure moments by deflection in...
G. E. Ballentine, G. F. Bertsch, N. Onishi, K. Yab...
We present an approach for accelerating hierarchical radiosity by clustering objects. Previous approaches constructed effective hierarchies by subdividing surfaces, but could not ...
Many clustering algorithms fail when dealing with high dimensional data. Principal component analysis (PCA) is a popular dimensionality reduction algorithm. However, it assumes a ...