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ICDAR
2009
IEEE
14 years 3 months ago
Evaluating Retraining Rules for Semi-Supervised Learning in Neural Network Based Cursive Word Recognition
Training a system to recognize handwritten words is a task that requires a large amount of data with their correct transcription. However, the creation of such a training set, inc...
Volkmar Frinken, Horst Bunke
ICASSP
2009
IEEE
14 years 3 months ago
Language model parameter estimation using user transcriptions
In limited data domains, many effective language modeling techniques construct models with parameters to be estimated on an in-domain development set. However, in some domains, no...
Bo-June Paul Hsu, James R. Glass
PKDD
2009
Springer
88views Data Mining» more  PKDD 2009»
14 years 3 months ago
Feature Weighting Using Margin and Radius Based Error Bound Optimization in SVMs
The Support Vector Machine error bound is a function of the margin and radius. Standard SVM algorithms maximize the margin within a given feature space, therefore the radius is fi...
Huyen Do, Alexandros Kalousis, Melanie Hilario
JMLR
2010
153views more  JMLR 2010»
13 years 3 months ago
Generalized Expectation Criteria for Semi-Supervised Learning with Weakly Labeled Data
In this paper, we present an overview of generalized expectation criteria (GE), a simple, robust, scalable method for semi-supervised training using weakly-labeled data. GE fits m...
Gideon S. Mann, Andrew McCallum
KDD
1998
ACM
102views Data Mining» more  KDD 1998»
14 years 19 days ago
Joins that Generalize: Text Classification Using WHIRL
WHIRL is an extensionof relational databasesthat canperform "soft joins" basedon the similarity of textual identifiers;thesesoftjoins extendthe traditional operationof j...
William W. Cohen, Haym Hirsh