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» Gaussian Processes for Machine Learning
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SIAMIS
2011
13 years 2 months ago
Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models
Abstract. Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or superresolution, can be addressed by maxi...
Matthias W. Seeger, Hannes Nickisch
SIGSOFT
2007
ACM
14 years 8 months ago
Recovering and using use-case-diagram-to-source-code traceability links
Use case diagrams (UCDs) are widely used to describe requirements and desired functionality of software products. However, UCDs are loosely linked to source code, and maintaining ...
Mark Grechanik, Kathryn S. McKinley, Dewayne E. Pe...
MOBISYS
2009
ACM
14 years 8 months ago
Sensor selection for energy-efficient ambulatory medical monitoring
Epilepsy affects over three million Americans of all ages. Despite recent advances, more than 20% of individuals with epilepsy never achieve adequate control of their seizures. Th...
Eugene Shih, Ali H. Shoeb, John V. Guttag
SIGMOD
2004
ACM
262views Database» more  SIGMOD 2004»
14 years 7 months ago
The Next Database Revolution
Database system architectures are undergoing revolutionary changes. Most importantly, algorithms and data are being unified by integrating programming languages with the database ...
Jim Gray
ER
2006
Springer
158views Database» more  ER 2006»
13 years 11 months ago
Database to Semantic Web Mapping Using RDF Query Languages
One of the main drawbacks of the Semantic Web is the lack of semantically rich data, since most of the information is still stored in relational databases. In this paper, we presen...
Cristian Pérez de Laborda, Stefan Conrad