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IJCAI
2003
15 years 4 months ago
Semi-Supervised Learning with Explicit Misclassification Modeling
This paper investigates a new approach for training discriminant classifiers when only a small set of labeled data is available together with a large set of unlabeled data. This a...
Massih-Reza Amini, Patrick Gallinari
ACL
2010
15 years 1 months ago
Experiments in Graph-Based Semi-Supervised Learning Methods for Class-Instance Acquisition
Graph-based semi-supervised learning (SSL) algorithms have been successfully used to extract class-instance pairs from large unstructured and structured text collections. However,...
Partha Pratim Talukdar, Fernando Pereira
115
Voted
COLING
2010
14 years 10 months ago
Grouping Product Features Using Semi-Supervised Learning with Soft-Constraints
In opinion mining of product reviews, one often wants to produce a summary of opinions based on product features/attributes. However, for the same feature, people can express it w...
Zhongwu Zhai, Bing Liu, Hua Xu, Peifa Jia
JMLR
2010
153views more  JMLR 2010»
14 years 10 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
128
Voted
JMLR
2010
119views more  JMLR 2010»
14 years 10 months ago
Semi-Supervised Learning via Generalized Maximum Entropy
Various supervised inference methods can be analyzed as convex duals of the generalized maximum entropy (MaxEnt) framework. Generalized MaxEnt aims to find a distribution that max...
Ayse Erkan, Yasemin Altun