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» Modeling the variability of architectural patterns
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GRC
2010
IEEE
15 years 26 days ago
Learning Multiple Latent Variables with Self-Organizing Maps
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
Lili Zhang, Erzsébet Merényi
101
Voted
WCRE
2003
IEEE
15 years 5 months ago
Extracting an Explicitly Data-Parallel Representation of Image-Processing Programs
Our research goal is to retarget image processing programs written in sequential languages (e.g., C) to architectures with data-parallel processing capabilities. Image processing ...
Lewis B. Baumstark Jr., Murat Guler, Linda M. Will...
SSR
2001
146views more  SSR 2001»
15 years 1 months ago
Implementing product line variabilities
Software product lines have numerous members. Thus, a product line infrastructure must cover various systems. This is the significant difference to usual software systems and the ...
Cristina Gacek, Michalis Anastasopoules
DAC
2007
ACM
16 years 23 days ago
Beyond Low-Order Statistical Response Surfaces: Latent Variable Regression for Efficient, Highly Nonlinear Fitting
The number and magnitude of process variation sources are increasing as we scale further into the nano regime. Today's most successful response surface methods limit us to lo...
Amith Singhee, Rob A. Rutenbar
DAC
2007
ACM
16 years 23 days ago
PV-PPV: Parameter Variability Aware, Automatically Extracted, Nonlinear Time-Shifted Oscillator Macromodels
Abstract-- The PPV is a robust phase domain macromodel for oscillators. It has been proven to predict oscillators' responses correctly under small signal perturbations, and ca...
Zhichun Wang, Xiaolue Lai, Jaijeet S. Roychowdhury