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SIAMIS
2011
14 years 11 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
NCA
2002
IEEE
15 years 3 months ago
Comparison of Algorithmic and Machine Learning Approaches for the Automatic Fitting of Gaussian Peaks
Fitting gaussian peaks to experimental data is important in many disciplines, including nuclear spectroscopy. Nonlinear least squares fitting methods have been in use for a long t...
Radwan E. Abdel-Aal
ISPD
2006
ACM
158views Hardware» more  ISPD 2006»
15 years 10 months ago
Effective linear programming based placement methods
Linear programming (LP) based methods are attractive for solving the placement problem because of their ability to model Half-Perimeter Wirelength (HPWL) and timing. However, it h...
Sherief Reda, Amit Chowdhary
CODES
2010
IEEE
15 years 2 months ago
Automatic parallelization of embedded software using hierarchical task graphs and integer linear programming
The last years have shown that there is no way to disregard the advantages provided by multiprocessor System-on-Chip (MPSoC) architectures in the embedded systems domain. Using mu...
Daniel Cordes, Peter Marwedel, Arindam Mallik
146
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SIAMSC
2010
120views more  SIAMSC 2010»
15 years 2 months ago
Weighted Matrix Ordering and Parallel Banded Preconditioners for Iterative Linear System Solvers
The emergence of multicore architectures and highly scalable platforms motivates the development of novel algorithms and techniques that emphasize concurrency and are tolerant of ...
Murat Manguoglu, Mehmet Koyutürk, Ahmed H. Sa...