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» A selective sampling approach to active feature selection
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MM
2004
ACM
151views Multimedia» more  MM 2004»
14 years 2 months ago
Multimodal concept-dependent active learning for image retrieval
It has been established that active learning is effective for learning complex, subjective query concepts for image retrieval. However, active learning has been applied in a conc...
Kingshy Goh, Edward Y. Chang, Wei-Cheng Lai
ISDA
2010
IEEE
13 years 7 months ago
Feature selection is the ReliefF for multiple instance learning
Dimensionality reduction and feature selection in particular are known to be of a great help for making supervised learning more effective and efficient. Many different feature sel...
Amelia Zafra, Mykola Pechenizkiy, Sebastián...
PAKDD
2005
ACM
114views Data Mining» more  PAKDD 2005»
14 years 2 months ago
Increasing Classification Accuracy by Combining Adaptive Sampling and Convex Pseudo-Data
The availability of microarray data has enabled several studies on the application of aggregated classifiers for molecular classification. We present a combination of classifier ag...
Chia Huey Ooi, Madhu Chetty
PRIB
2010
Springer
242views Bioinformatics» more  PRIB 2010»
13 years 7 months ago
Consensus of Ambiguity: Theory and Application of Active Learning for Biomedical Image Analysis
Abstract. Supervised classifiers require manually labeled training samples to classify unlabeled objects. Active Learning (AL) can be used to selectively label only “ambiguous...
Scott Doyle, Anant Madabhushi
CN
2006
85views more  CN 2006»
13 years 9 months ago
An efficient heuristic for selecting active nodes in wireless sensor networks
Energy saving is a paramount concern in wireless sensor networks (WSNs). A strategy for energy saving is to cleverly manage the duty cycle of sensors, by dynamically activating di...
Flávia Coimbra Delicato, Fábio Prott...