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» Learning Gaussian processes from multiple tasks
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180
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CVPR
2011
IEEE
14 years 7 months ago
Nonlinear Shape Manifolds as Shape Priors in Level Set Segmentation and Tracking
We propose a novel nonlinear, probabilistic and variational method for adding shape information to level setbased segmentation and tracking. Unlike previous work, we represent sha...
Victor Prisacariu, Ian Reid
DATE
2009
IEEE
107views Hardware» more  DATE 2009»
15 years 10 months ago
Learning early-stage platform dimensioning from late-stage timing verification
— Today's innovations in the automotive sector are, to a great extent, based on electronics. The increasing integration complexity and stringent cost reduction goals turn E/...
Kai Richter, Marek Jersak, Rolf Ernst
100
Voted
ICAPR
2005
Springer
15 years 9 months ago
Discovering Predictive Variables When Evolving Cognitive Models
A non-dominated sorting genetic algorithm is used to evolve models of learning from different theories for multiple tasks. Correlation analysis is performed to identify parameters...
Peter C. R. Lane, Fernand Gobet
122
Voted
PODC
2010
ACM
15 years 7 months ago
The multiplicative power of consensus numbers
: The Borowsky-Gafni (BG) simulation algorithm is a powerful reduction algorithm that shows that t-resilience of decision tasks can be fully characterized in terms of wait-freedom....
Damien Imbs, Michel Raynal
132
Voted
SC
2009
ACM
15 years 10 months ago
Lessons learned from a year's worth of benchmarks of large data clouds
In this paper, we discuss some of the lessons that we have learned working with the Hadoop and Sector/Sphere systems. Both of these systems are cloud-based systems designed to sup...
Yunhong Gu, Robert L. Grossman