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» A selective sampling approach to active feature selection
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IAJIT
2008
207views more  IAJIT 2008»
13 years 10 months ago
Neural Networks and Support Vector Machines Classifiers for Writer Identification Using Arabic Script
: In this paper, we present an approach for writer identification carried out using off-line Arabic handwriting. Our proposed method is based on the combination of global and struc...
Sami Gazzah, Najoua Essoukri Ben Amara
SDM
2008
SIAM
136views Data Mining» more  SDM 2008»
13 years 11 months ago
Exploration and Reduction of the Feature Space by Hierarchical Clustering
In this paper we propose and test the use of hierarchical clustering for feature selection. The clustering method is Ward's with a distance measure based on GoodmanKruskal ta...
Dino Ienco, Rosa Meo
CSL
2010
Springer
13 years 10 months ago
Active learning and semi-supervised learning for speech recognition: A unified framework using the global entropy reduction maxi
We propose a unified global entropy reduction maximization (GERM) framework for active learning and semi-supervised learning for speech recognition. Active learning aims to select...
Dong Yu, Balakrishnan Varadarajan, Li Deng, Alex A...
IJON
2007
131views more  IJON 2007»
13 years 10 months ago
Margin-based active learning for LVQ networks
In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples and thereby increase speed a...
Frank-Michael Schleif, Barbara Hammer, Thomas Vill...
ACL
2008
13 years 11 months ago
Multi-Task Active Learning for Linguistic Annotations
We extend the classical single-task active learning (AL) approach. In the multi-task active learning (MTAL) paradigm, we select examples for several annotation tasks rather than f...
Roi Reichart, Katrin Tomanek, Udo Hahn, Ari Rappop...