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» Approximate algorithms for neural-Bayesian approaches
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CAV
2006
Springer
165views Hardware» more  CAV 2006»
15 years 1 months ago
Bounded Model Checking of Concurrent Data Types on Relaxed Memory Models: A Case Study
Many multithreaded programs employ concurrent data types to safely share data among threads. However, highly-concurrent algorithms for even seemingly simple data types are difficul...
Sebastian Burckhardt, Rajeev Alur, Milo M. K. Mart...
COCO
2006
Springer
93views Algorithms» more  COCO 2006»
15 years 1 months ago
Making Hard Problems Harder
We consider a general approach to the hoary problem of (im)proving circuit lower bounds. We define notions of hardness condensing and hardness extraction, in analogy to the corres...
Joshua Buresh-Oppenheim, Rahul Santhanam
66
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KDD
2010
ACM
188views Data Mining» more  KDD 2010»
14 years 11 months ago
Inferring networks of diffusion and influence
Information diffusion and virus propagation are fundamental processes talking place in networks. While it is often possible to directly observe when nodes become infected, observi...
Manuel Gomez-Rodriguez, Jure Leskovec, Andreas Kra...
BMCBI
2008
139views more  BMCBI 2008»
14 years 9 months ago
The C1C2: A framework for simultaneous model selection and assessment
Background: There has been recent concern regarding the inability of predictive modeling approaches to generalize to new data. Some of the problems can be attributed to improper m...
Martin Eklund, Ola Spjuth, Jarl E. S. Wikberg
CORR
2010
Springer
210views Education» more  CORR 2010»
14 years 9 months ago
Exploiting Statistical Dependencies in Sparse Representations for Signal Recovery
Signal modeling lies at the core of numerous signal and image processing applications. A recent approach that has drawn considerable attention is sparse representation modeling, in...
Tomer Faktor, Yonina C. Eldar, Michael Elad