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122
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CORR
2010
Springer
153views Education» more  CORR 2010»
15 years 2 months ago
GraphLab: A New Framework for Parallel Machine Learning
Designing and implementing efficient, provably correct parallel machine learning (ML) algorithms is challenging. Existing high-level parallel abstractions like MapReduce are insuf...
Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny B...
ICCV
2009
IEEE
15 years 10 days ago
Real-time visual tracking via Incremental Covariance Tensor Learning
Visual tracking is a challenging problem, as an object may change its appearance due to pose variations, illumination changes, and occlusions. Many algorithms have been proposed t...
Yi Wu, Jian Cheng, Jinqiao Wang, Hanqing Lu
104
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JMLR
2010
117views more  JMLR 2010»
14 years 9 months ago
Bayesian Online Learning for Multi-label and Multi-variate Performance Measures
Many real world applications employ multivariate performance measures and each example can belong to multiple classes. The currently most popular approaches train an SVM for each ...
Xinhua Zhang, Thore Graepel, Ralf Herbrich
71
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DATE
2003
IEEE
82views Hardware» more  DATE 2003»
15 years 8 months ago
A Circuit SAT Solver With Signal Correlation Guided Learning
— Boolean Satistifiability has attracted tremendous research effort in recent years, resulting in the developments of various efficient SAT solver packages. Based upon their de...
Feng Lu, Li-C. Wang, Kwang-Ting Cheng, Ric C.-Y. H...
119
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EUROGP
1999
Springer
151views Optimization» more  EUROGP 1999»
15 years 6 months ago
Phenotype Plasticity in Genetic Programming: A Comparison of Darwinian and Lamarckian Inheritance Schemes
Abstract We consider a form of phenotype plasticity in Genetic Programming (GP). This takes the form of a set of real-valued numerical parameters associated with each individual, a...
Anna Esparcia-Alcázar, Ken Sharman