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ICDAR
2009
IEEE
15 years 11 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
15 years 11 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»
15 years 11 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
153
Voted
JMLR
2010
153views more  JMLR 2010»
14 years 11 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
109
Voted
KDD
1998
ACM
102views Data Mining» more  KDD 1998»
15 years 9 months 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