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TSP
2010
13 years 2 months ago
Variance-component based sparse signal reconstruction and model selection
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
Kun Qiu, Aleksandar Dogandzic
BMCBI
2011
13 years 2 months ago
Removing Noise From Pyrosequenced Amplicons
Background: In many environmental genomics applications a homologous region of DNA from a diverse sample is first amplified by PCR and then sequenced. The next generation sequenci...
Christopher Quince, Anders Lanzén, Russell ...
DATE
2009
IEEE
105views Hardware» more  DATE 2009»
14 years 2 months ago
Enrichment of limited training sets in machine-learning-based analog/RF test
Abstract— This paper discusses the generation of informationrich, arbitrarily-large synthetic data sets which can be used to (a) efficiently learn tests that correlate a set of ...
Haralampos-G. D. Stratigopoulos, Salvador Mir, Yio...
ICDT
2001
ACM
116views Database» more  ICDT 2001»
14 years 5 days ago
On Optimizing Nearest Neighbor Queries in High-Dimensional Data Spaces
Abstract. Nearest-neighbor queries in high-dimensional space are of high importance in various applications, especially in content-based indexing of multimedia data. For an optimiz...
Stefan Berchtold, Christian Böhm, Daniel A. K...
CIKM
2009
Springer
14 years 11 days ago
Probabilistic models for topic learning from images and captions in online biomedical literatures
Biomedical images and captions are one of the major sources of information in online biomedical publications. They often contain the most important results to be reported, and pro...
Xin Chen, Caimei Lu, Yuan An, Palakorn Achananupar...