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» Making inferences with small numbers of training sets
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BMCBI
2008
175views more  BMCBI 2008»
14 years 12 months ago
Synonym set extraction from the biomedical literature by lexical pattern discovery
Background: Although there are a large number of thesauri for the biomedical domain many of them lack coverage in terms and their variant forms. Automatic thesaurus construction b...
John McCrae, Nigel Collier
NIPS
1998
15 years 1 months ago
Efficient Bayesian Parameter Estimation in Large Discrete Domains
In this paper we examine the problem of estimating the parameters of a multinomial distribution over a large number of discreteoutcomes,most of which do not appearin the training ...
Nir Friedman, Yoram Singer
PR
2006
102views more  PR 2006»
14 years 11 months ago
Prototype selection for dissimilarity-based classifiers
A conventional way to discriminate between objects represented by dissimilarities is the nearest neighbor method. A more efficient and sometimes a more accurate solution is offere...
Elzbieta Pekalska, Robert P. W. Duin, Pavel Pacl&i...
ICDM
2008
IEEE
137views Data Mining» more  ICDM 2008»
15 years 6 months ago
Iterative Set Expansion of Named Entities Using the Web
Set expansion refers to expanding a partial set of “seed” objects into a more complete set. One system that does set expansion is SEAL (Set Expander for Any Language), which e...
Richard C. Wang, William W. Cohen
CVPR
2006
IEEE
16 years 1 months ago
Incorporating the Boltzmann Prior in Object Detection Using SVM
In this paper we discuss object detection when only a small number of training examples are given. Specifically, we show how to incorporate a simple prior on the distribution of n...
Margarita Osadchy, Daniel Keren