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Active learning (machine learning)

Known as: Pool-based active learning 
Active learning is a special case of semi-supervised machine learning in which a learning algorithm is able to interactively query the user (or some… 
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Bayesian experimental designCold startEvolving intelligent systemList of datasets for machine learning research

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Machine learning

Papers overview

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2017
2017
Active learning for low-resource speech recognition: Impact of selection size and language modeling data
Active learning aims to reduce the time and cost of developing speech recognition systems by selecting for transcription highly… 
2012
2012
Incremental Sparse Bayesian Method for Online Dialog Strategy Learning
This paper proposes an incremental sparse Bayesian learning method to allow continuous dialog strategy learning from the… 
Review
2010
Review
2010
Quit Surfing and Start "Clicking": One Professor's Effort to Combat the Problems of Teaching the U.S. Survey in a Large Lecture Hall
Teaching an introductory survey course in a typical lecture hall presents a series of related obstacles. The large number of… 
2009
2009
Conflictos en el trabajo en grupo: cuatro casos habituales
espanolEste articulo describe cuatro casos representativos de conflictos entre los miembros de un grupo cuando se utilizan… 
2009
2009
Spatially Adaptive Classification and Active Learning of Multispectral Data with Gaussian Processes
Multispectral remote sensing images are widely used for automated land use and land cover classification tasks. Remotely sensed… 
2009
2009
Multiple-Instance Active Learning for Image Categorization
Both multiple-instance learning and active learning are widely employed in image categorization, but generally they are applied… 
2006
2006
Multi-Criterion Active Learning in Conditional Random Fields
Conditional random fields (CRFs), which are popular supervised learning models for many natural language processing (NLP) tasks… 
Highly Cited
2005
Highly Cited
2005
Semi-automatic video annotation based on active learning with multiple complementary predictors
In this paper, we will propose a novel semi-automatic annotation scheme for video semantic classification. It is well known that… 
2005
2005
Labeling of Textured Data with Co-training and Active Learning
In this paper, we present a robust texture labeling method that requires minimum user interaction. Initially only a fraction of… 
2003
2003
Active Learning for Statistical Machine Translation
Disclosed is a training projectile having the same ballistic characteristic as the operational projectile. The training…