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» Learning from Multiple Annotators with Gaussian Processes
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ICASSP
2011
IEEE
14 years 3 months ago
Using the kernel trick in compressive sensing: Accurate signal recovery from fewer measurements
Compressive sensing accurately reconstructs a signal that is sparse in some basis from measurements, generally consisting of the signal’s inner products with Gaussian random vec...
Hanchao Qi, Shannon Hughes
SIGMOD
2011
ACM
242views Database» more  SIGMOD 2011»
14 years 2 months ago
The SystemT IDE: an integrated development environment for information extraction rules
Information Extraction (IE) — the problem of extracting structured information from unstructured text — has become the key enabler for many enterprise applications such as sem...
Laura Chiticariu, Vivian Chu, Sajib Dasgupta, Thil...
AMAI
2004
Springer
15 years 5 months ago
Using the Central Limit Theorem for Belief Network Learning
Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
Ian Davidson, Minoo Aminian
ICMCS
2007
IEEE
155views Multimedia» more  ICMCS 2007»
15 years 6 months ago
Hidden Maximum Entropy Approach for Visual Concept Modeling
Recently, the bag-of-words approach has been successfully applied to automatic image annotation, object recognition, etc. The method needs to first quantize an image using the vis...
Sheng Gao, Joo-Hwee Lim, Qibin Sun
ICPR
2006
IEEE
16 years 29 days ago
Extracting Lines in Noisy Image Using Directional Information
Detection of lines in noisy image is not easy. When using Hough transform, multiple false peaks may be generated from collinear noisy edge points, which in turn may create false l...
Arturo Sanchez-Azofeifa, Jun Zhou, Walter F. Bisch...