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JCST
2010
189views more  JCST 2010»
14 years 9 months ago
Formally Analyzing Expected Time Complexity of Algorithms Using Theorem Proving
Probabilistic techniques are widely used in the analysis of algorithms to estimate the computational complexity of algorithms or a computational problem. Traditionally, such analys...
Osman Hasan, Sofiène Tahar
TC
2008
15 years 2 months ago
Optimal and Practical Algorithms for Sorting on the PDM
Abstract. The Parallel Disks Model (PDM) has been proposed to alleviate the I/O bottleneck that arises in the processing of massive data sets. Sorting has been extensively studied ...
Sanguthevar Rajasekaran, Sandeep Sen
279
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5396views
17 years 1 months ago
Markov Random Field Modeling in Computer Vision
Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
Stan Z. Li
CVPR
2009
IEEE
16 years 9 months ago
Global Connectivity Potentials for Random Field Models
Markov random field (MRF, CRF) models are popular in computer vision. However, in order to be computationally tractable they are limited to incorporate only local interactions a...
Sebastian Nowozin, Christoph H. Lampert
ICCV
2009
IEEE
16 years 7 months ago
Semi-Supervised Random Forests
Random Forests (RFs) have become commonplace in many computer vision applications. Their popularity is mainly driven by their high computational efficiency during both training ...
Christian Leistner, Amir Saffari, Jakob Santner, H...