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» Optimizing for parallelism and data locality
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UAI
2000
15 years 2 months ago
Exploiting Qualitative Knowledge in the Learning of Conditional Probabilities of Bayesian Networks
Algorithms for learning the conditional probabilities of Bayesian networks with hidden variables typically operate within a high-dimensional search space and yield only locally op...
Frank Wittig, Anthony Jameson
93
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NIPS
1992
15 years 1 months ago
Some Solutions to the Missing Feature Problem in Vision
In visual processing the ability to deal with missing and noisy information is crucial. Occlusions and unreliable feature detectors often lead to situations where little or no dir...
Subutai Ahmad, Volker Tresp
COGSCI
2010
234views more  COGSCI 2010»
15 years 23 days ago
High Regularities in Eye-Movement Patterns Reveal the Dynamics of the Visual Working Memory Allocation Mechanism
With only two to five slots of visual working memory (VWM), humans are able to quickly solve complex visual problems to near optimal solutions. To explain the paradox between tigh...
Xiaohui Kong, Christian D. Schunn, Garrick L. Wall...
95
Voted
AUTOMATICA
2005
112views more  AUTOMATICA 2005»
15 years 17 days ago
Robust maximum-likelihood estimation of multivariable dynamic systems
This paper examines the problem of estimating linear time-invariant state-space system models. In particular it addresses the parametrization and numerical robustness concerns tha...
Stuart Gibson, Brett Ninness
TKDE
2008
115views more  TKDE 2008»
15 years 17 days ago
A Niching Memetic Algorithm for Simultaneous Clustering and Feature Selection
Clustering is inherently a difficult task and is made even more difficult when the selection of relevant features is also an issue. In this paper, we propose an approach for simult...
Weiguo Sheng, Xiaohui Liu, Michael C. Fairhurst