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» Is an ordinal class structure useful in classifier learning
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ACL
2010
13 years 5 months ago
Inducing Domain-Specific Semantic Class Taggers from (Almost) Nothing
This research explores the idea of inducing domain-specific semantic class taggers using only a domain-specific text collection and seed words. The learning process begins by indu...
Ruihong Huang, Ellen Riloff
ICML
2006
IEEE
14 years 8 months ago
Cost-sensitive learning with conditional Markov networks
There has been a recent, growing interest in classification and link prediction in structured domains. Methods such as conditional random fields and relational Markov networks sup...
Prithviraj Sen, Lise Getoor
CORR
2011
Springer
183views Education» more  CORR 2011»
12 years 11 months ago
Learning When Training Data are Costly: The Effect of Class Distribution on Tree Induction
For large, real-world inductive learning problems, the number of training examples often must be limited due to the costs associated with procuring, preparing, and storing the tra...
Foster J. Provost, Gary M. Weiss
NAACL
2003
13 years 8 months ago
Active Learning for Classifying Phone Sequences from Unsupervised Phonotactic Models
This paper describes an application of active learning methods to the classification of phone strings recognized using unsupervised phonotactic models. The only training data req...
Shona Douglas
FC
2009
Springer
67views Cryptology» more  FC 2009»
13 years 11 months ago
Privacy-Preserving Classifier Learning
We present an efficient protocol for the privacy-preserving, distributed learning of decision-tree classifiers. Our protocol allows a user to construct a classifier on a database h...
Justin Brickell, Vitaly Shmatikov