Algorithms based on simulating stochastic flows are a simple and natural solution for the problem of clustering graphs, but their widespread use has been hampered by their lack of...
Clustering methods for data-mining problems must be extremely scalable. In addition, several data mining applications demand that the clusters obtained be balanced, i.e., be of ap...
Background: The Medium-chain Dehydrogenases/Reductases (MDR) form a protein superfamily whose size and complexity defeats traditional means of subclassification; it currently has ...
In this paper, we proposed a fast and accurate human pose estimation framework that combines top-down and bottom-up methods. The framework consists of an initialization stage and a...
Yanchao Su, Haizhou Ai, Takayoshi Yamashita, Shiho...
We present a novel anytime version of partitional clustering algorithm, such as k-Means and EM, for time series. The algorithm works by leveraging off the multi-resolution property...
Jessica Lin, Michail Vlachos, Eamonn J. Keogh, Dim...