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2004
Springer
15 years 10 months ago
Semi-supervised Learning from Unbalanced Labeled Data - An Improvement
Abstract. We present a possibly great improvement while performing semisupervised learning tasks from training data sets when only a small fraction of the data pairs is labeled. In...
Te Ming Huang, Vojislav Kecman
IJCNLP
2004
Springer
15 years 10 months ago
Combining Labeled and Unlabeled Data for Learning Cross-Document Structural Relationships
Multi-document discourse analysis has emerged with the potential of improving various NLP applications. Based on the newly proposed Cross-document Structure Theory (CST), this pap...
Zhu Zhang, Dragomir R. Radev
ICPR
2010
IEEE
15 years 3 months ago
Learning Image Anchor Templates for Document Classification and Data Extraction
Image anchor templates are used in document image analysis for document classification, data localization, and other tasks. Current tools allow human operators to mark out small s...
Prateek Sarkar
UAI
1998
15 years 6 months ago
A Multivariate Discretization Method for Learning Bayesian Networks from Mixed Data
In this paper we address the problem of discretization in the context of learning Bayesian networks (BNs) from data containing both continuous and discrete variables. We describe ...
Stefano Monti, Gregory F. Cooper
AIED
2005
Springer
15 years 10 months ago
Inferring learning and attitudes from a Bayesian Network of log file data
A student's goals and attitudes while interacting with a tutor are typically unseen and unknowable. However their outward behavior (e.g. problem-solving time, mistakes and hel...
Ivon Arroyo, Beverly Park Woolf