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» Active Learning by Labeling Features
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EMNLP
2009
13 years 2 months ago
Active Learning by Labeling Features
Methods that learn from prior information about input features such as generalized expectation (GE) have been used to train accurate models with very little effort. In this paper,...
Gregory Druck, Burr Settles, Andrew McCallum
PKDD
2010
Springer
143views Data Mining» more  PKDD 2010»
13 years 2 months ago
A Unified Approach to Active Dual Supervision for Labeling Features and Examples
Abstract. When faced with the task of building accurate classifiers, active learning is often a beneficial tool for minimizing the requisite costs of human annotation. Traditional ...
Josh Attenberg, Prem Melville, Foster J. Provost
ECCV
2008
Springer
14 years 6 months ago
Learning to Recognize Activities from the Wrong View Point
Appearance features are good at discriminating activities in a fixed view, but behave poorly when aspect is changed. We describe a method to build features that are highly stable u...
Ali Farhadi, Mostafa Kamali Tabrizi
PAMI
2006
143views more  PAMI 2006»
13 years 4 months ago
Variational Bayes for Continuous Hidden Markov Models and Its Application to Active Learning
In this paper we present a variational Bayes (VB) framework for learning continuous hidden Markov models (CHMMs), and we examine the VB framework within active learning. Unlike a ...
Shihao Ji, Balaji Krishnapuram, Lawrence Carin
ICML
2009
IEEE
14 years 5 months ago
Uncertainty sampling and transductive experimental design for active dual supervision
Dual supervision refers to the general setting of learning from both labeled examples as well as labeled features. Labeled features are naturally available in tasks such as text c...
Vikas Sindhwani, Prem Melville, Richard D. Lawrenc...