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» Combining programs and state machines
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PVLDB
2008
182views more  PVLDB 2008»
13 years 8 months ago
SCOPE: easy and efficient parallel processing of massive data sets
Companies providing cloud-scale services have an increasing need to store and analyze massive data sets such as search logs and click streams. For cost and performance reasons, pr...
Ronnie Chaiken, Bob Jenkins, Per-Åke Larson,...
MIR
2010
ACM
207views Multimedia» more  MIR 2010»
13 years 7 months ago
Learning to rank for content-based image retrieval
In Content-based Image Retrieval (CBIR), accurately ranking the returned images is of paramount importance, since users consider mostly the topmost results. The typical ranking st...
Fabio F. Faria, Adriano Veloso, Humberto Mossri de...
ASPLOS
2009
ACM
14 years 9 months ago
TwinDrivers: semi-automatic derivation of fast and safe hypervisor network drivers from guest OS drivers
In a virtualized environment, device drivers are often run inside a virtual machine (VM) rather than in the hypervisor, for reasons of safety and reduction in software engineering...
Aravind Menon, Simon Schubert, Willy Zwaenepoel
KDD
2008
ACM
181views Data Mining» more  KDD 2008»
14 years 9 months ago
Learning subspace kernels for classification
Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...
SC
2009
ACM
14 years 3 months ago
Autotuning multigrid with PetaBricks
Algorithmic choice is essential in any problem domain to realizing optimal computational performance. Multigrid is a prime example: not only is it possible to make choices at the ...
Cy P. Chan, Jason Ansel, Yee Lok Wong, Saman P. Am...