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ESOP
2011
Springer
14 years 6 months ago
Measure Transformer Semantics for Bayesian Machine Learning
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Johannes Borgström, Andrew D. Gordon, Michael...
CGF
2008
98views more  CGF 2008»
15 years 3 months ago
Texture Synthesis From Photographs
The goal of texture synthesis is to generate an arbitrarily large high-quality texture from a small input sample. Generally, it is assumed that the input image is given as a flat,...
Christian Eisenacher, Sylvain Lefebvre, Marc Stamm...
CVPR
2010
IEEE
15 years 8 months ago
Learning 3D Action Models from a few 2D videos for View Invariant Action Recognition
Most existing approaches for learning action models work by extracting suitable low-level features and then training appropriate classifiers. Such approaches require large amount...
Pradeep Natarajan, Vivek Singh, Ram Nevatia
MM
2009
ACM
277views Multimedia» more  MM 2009»
15 years 9 months ago
Inferring semantic concepts from community-contributed images and noisy tags
In this paper, we exploit the problem of inferring images’ semantic concepts from community-contributed images and their associated noisy tags. To infer the concepts more accura...
Jinhui Tang, Shuicheng Yan, Richang Hong, Guo-Jun ...
AUTOMATICA
2004
91views more  AUTOMATICA 2004»
15 years 2 months ago
Comparing digital implementation via the bilinear and step-invariant transformations
From an analog system K, digital systems Kd and Kbt are often obtained via the step-invariant and bilinear transformations, respectively. For the case when K is stable, it is show...
Guofeng Zhang, Tongwen Chen