— We target the problem of predicting resource usage in situations where the modeling data is scarce, non-stationary, or expensive to obtain. This scenario occurs frequently in c...
Supervised learning on sequence data, also known as sequence classification, has been well recognized as an important data mining task with many significant applications. Since te...
Zhengzheng Xing, Jian Pei, Guozhu Dong, Philip S. ...
We introduce an algorithm for approximating a 2manifold 3D mesh by a set of developable surfaces. Each developable surface is a generalized cylinder represented as a strip of tria...
We present a framework for segmenting and storing filament networks from scalar volume data. Filament structures are commonly found in data generated using high-throughput microsc...
We propose a novel classification approach for automatically detecting pulmonary embolism (PE) from computedtomography-angiography images. Unlike most existing approaches that req...