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» Making inferences with small numbers of training sets
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BMCBI
2005
152views more  BMCBI 2005»
13 years 7 months ago
Ranking the whole MEDLINE database according to a large training set using text indexing
Background: The MEDLINE database contains over 12 million references to scientific literature, ut 3/4 of recent articles including an abstract of the publication. Retrieval of ent...
Brian P. Suomela, Miguel A. Andrade
AMR
2007
Springer
203views Multimedia» more  AMR 2007»
14 years 1 months ago
Automatic Image Annotation Using a Visual Dictionary Based on Reliable Image Segmentation
Recent approaches in Automatic Image Annotation (AIA) try to combine the expressiveness of natural language queries with approaches to minimize the manual effort for image annotat...
Christian Hentschel, Sebastian Stober, Andreas N&u...
JMLR
2012
11 years 10 months ago
Domain Adaptation: A Small Sample Statistical Approach
We study the prevalent problem when a test distribution differs from the training distribution. We consider a setting where our training set consists of a small number of sample d...
Ruslan Salakhutdinov, Sham M. Kakade, Dean P. Fost...
ICPR
2008
IEEE
14 years 2 months ago
RANSAC-SVM for large-scale datasets
Support Vector Machines (SVMs), though accurate, are still difficult to solve large-scale applications, due to the computational and storage requirement. To relieve this problem,...
Kenji Watanabe, Takio Kurita
BMCBI
2010
148views more  BMCBI 2010»
13 years 7 months ago
Applying unmixing to gene expression data for tumor phylogeny inference
Background: While in principle a seemingly infinite variety of combinations of mutations could result in tumor development, in practice it appears that most human cancers fall int...
Russell Schwartz, Stanley Shackney