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» On Variations of Power Iteration
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CVPR
2007
IEEE
15 years 8 days ago
Utilizing Variational Optimization to Learn Markov Random Fields
Markov Random Field, or MRF, models are a powerful tool for modeling images. While much progress has been made in algorithms for inference in MRFs, learning the parameters of an M...
Marshall F. Tappen
DAC
2006
ACM
14 years 11 months ago
An adaptive FPGA architecture with process variation compensation and reduced leakage
Process induced threshold voltage variations bring about fluctuations in circuit delay, that affect the FPGA timing yield. We propose an adaptive FPGA architecture that compensate...
Georges Nabaa, Navid Azizi, Farid N. Najm
BMCBI
2006
143views more  BMCBI 2006»
13 years 10 months ago
Application of protein structure alignments to iterated hidden Markov model protocols for structure prediction
Background: One of the most powerful methods for the prediction of protein structure from sequence information alone is the iterative construction of profile-type models. Because ...
Eric D. Scheeff, Philip E. Bourne
ASPDAC
2009
ACM
161views Hardware» more  ASPDAC 2009»
14 years 4 months ago
Risk aversion min-period retiming under process variations
— Recent advances in statistical timing analysis (SSTA) achieve great success in computing arrival times under variations by extending sum and maximum operations to random variab...
Jia Wang, Hai Zhou
ISLPED
2007
ACM
97views Hardware» more  ISLPED 2007»
13 years 11 months ago
Detailed placement for leakage reduction using systematic through-pitch variation
We present a novel detailed placement technique that accounts for systematic through-pitch variations to reduce leakage. Leakage depends nearly exponentially on linewidth (gate le...
Andrew B. Kahng, Swamy Muddu, Puneet Sharma