Principal ComponentAnalysis (PCA) has been successfully applied to construct linear models of shape, graylevel, and motion. In particular, PCA has been widely used to model the var...
Traditional problem determination techniques rely on static dependency models that are difficult to generate accurately in today’s large, distributed, and dynamic application e...
Mike Y. Chen, Emre Kiciman, Eugene Fratkin, Armand...
We describe a machine learning approach for predicting sponsored search ad relevance. Our baseline model incorporates basic features of text overlap and we then extend the model t...
Dustin Hillard, Stefan Schroedl, Eren Manavoglu, H...
We demonstrate how Field Programmable Gate Arrays (FPGAs) may be used to address the computing challenges associated with assembling genome sequences from recent ultra-high-through...
Kristian Stevens, Henry Chen, Terry Filiba, Peter ...
The bioactivity of a molecule strongly depends on its metastable conformational shapes and the transitions between these. Therefore, conformation analysis and visualization is a b...
Johannes Schmidt-Ehrenberg, Daniel Baum, Hans-Chri...