A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Scientific data are posing new challenges to data management due to the large volume, complexity and heterogeneity of the data. Meanwhile, scientific collaboration becomes increas...
Fusheng Wang, Pierre-Emmanuel Bourgue, Georg Hacke...
We present a Dynamic Data Driven Application System (DDDAS) to track 2D shapes across large pose variations by learning non-linear shape manifold as overlapping, piecewise linear s...
The architectural design of embedded systems is becoming increasingly idiosyncratic to meet varying constraints regarding energy consumption, code size, and execution time. Tradit...