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FTCGV
2011
122views more  FTCGV 2011»
14 years 8 months ago
Structured Learning and Prediction in Computer Vision
Powerful statistical models that can be learned efficiently from large amounts of data are currently revolutionizing computer vision. These models possess a rich internal structur...
Sebastian Nowozin, Christoph H. Lampert
ICPP
2006
IEEE
15 years 10 months ago
Performance Modeling based on Multidimensional Surface Learning for Performance Predictions of Parallel Applications in Non-Dedi
Modeling the performance behavior of parallel applications to predict the execution times of the applications for larger problem sizes and number of processors has been an active ...
Jay Yagnik, H. A. Sanjay, Sathish S. Vadhiyar
EC
2010
176views ECommerce» more  EC 2010»
15 years 1 months ago
Learning Factorizations in Estimation of Distribution Algorithms Using Affinity Propagation
Estimation of distribution algorithms (EDAs) that use marginal product model factorizations have been widely applied to a broad range of, mainly binary, optimization problems. In ...
Roberto Santana, Pedro Larrañaga, Jos&eacut...
ICML
2007
IEEE
16 years 5 months ago
Linear and nonlinear generative probabilistic class models for shape contours
We introduce a robust probabilistic approach to modeling shape contours based on a lowdimensional, nonlinear latent variable model. In contrast to existing techniques that use obj...
Graham McNeill, Sethu Vijayakumar
CVPR
2008
IEEE
16 years 6 months ago
Who killed the directed model?
Prior distributions are useful for robust low-level vision, and undirected models (e.g. Markov Random Fields) have become a central tool for this purpose. Though sometimes these p...
Justin Domke, Alap Karapurkar, Yiannis Aloimonos