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» Recognizing Unnecessary Inference
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POPL
2006
ACM
14 years 7 months ago
Autolocker: synchronization inference for atomic sections
The movement to multi-core processors increases the need for simpler, more robust parallel programming models. Atomic sections have been widely recognized for their ease of use. T...
Bill McCloskey, Feng Zhou, David Gay, Eric A. Brew...
JCST
2010
139views more  JCST 2010»
13 years 5 months ago
Dirichlet Process Gaussian Mixture Models: Choice of the Base Distribution
In the Bayesian mixture modeling framework it is possible to infer the necessary number of components to model the data and therefore it is unnecessary to explicitly restrict the n...
Dilan Görür, Carl Edward Rasmussen
CVPR
2007
IEEE
14 years 9 months ago
Objects in Action: An Approach for Combining Action Understanding and Object Perception
Analysis of videos of human-object interactions involves understanding human movements, locating and recognizing objects and observing the effects of human movements on those obje...
Abhinav Gupta, Larry S. Davis
SDM
2008
SIAM
138views Data Mining» more  SDM 2008»
13 years 8 months ago
Learning Markov Network Structure using Few Independence Tests
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
Parichey Gandhi, Facundo Bromberg, Dimitris Margar...
CVPR
2007
IEEE
14 years 9 months ago
Fast Keypoint Recognition in Ten Lines of Code
While feature point recognition is a key component of modern approaches to object detection, existing approaches require computationally expensive patch preprocessing to handle pe...
Mustafa Özuysal, Pascal Fua, Vincent Lepetit