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» Active learning with extremely sparse labeled examples
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180
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CVPR
2010
IEEE
16 years 2 months ago
Breaking the interactive bottleneck in multi-class classification with active selection and binary feedback
Multi-class classification schemes typically require human input in the form of precise category names or numbers for each example to be annotated – providing this can be impra...
Ajay Joshi, Fatih Porikli, Nikolaos Papanikolopoul...
ACL
2006
15 years 8 months ago
Prototype-Driven Grammar Induction
We investigate prototype-driven learning for primarily unsupervised grammar induction. Prior knowledge is specified declaratively, by providing a few canonical examples of each ta...
Aria Haghighi, Dan Klein
175
Voted
MIR
2003
ACM
178views Multimedia» more  MIR 2003»
15 years 12 months ago
A bootstrapping approach to annotating large image collection
Huge amount of manual efforts are required to annotate large image/video archives with text annotations. Several recent works attempted to automate this task by employing supervis...
HuaMin Feng, Tat-Seng Chua
AAAI
2000
15 years 8 months ago
Selective Sampling with Redundant Views
Selective sampling, a form of active learning, reduces the cost of labeling training data by asking only for the labels of the most informative unlabeled examples. We introduce a ...
Ion Muslea, Steven Minton, Craig A. Knoblock
175
Voted
ISMIS
1999
Springer
15 years 11 months ago
Machine Learning Method for Software Quality Model Building
Software quality prediction can be cast as a concept learning problem. In this paper, we discuss the full cycle of an application of Machine Learning to software quality predictio...
Mauricio Amaral de Almeida, Stan Matwin