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ACL
2008
13 years 6 months ago
Active Learning with Confidence
Active learning is a machine learning approach to achieving high-accuracy with a small amount of labels by letting the learning algorithm choose instances to be labeled. Most of p...
Mark Dredze, Koby Crammer
EMNLP
2010
13 years 2 months ago
Confidence in Structured-Prediction Using Confidence-Weighted Models
Confidence-Weighted linear classifiers (CW) and its successors were shown to perform well on binary and multiclass NLP problems. In this paper we extend the CW approach for sequen...
Avihai Mejer, Koby Crammer
GECCO
2009
Springer
188views Optimization» more  GECCO 2009»
13 years 8 months ago
Exploiting multiple classifier types with active learning
Many approaches to active learning involve training one classifier by periodically choosing new data points about which the classifier has the least confidence, but designing a co...
Zhenyu Lu, Josh Bongard
CVPR
2010
IEEE
14 years 1 months ago
Beyond Active Noun Tagging: Modeling Contextual Interactions for Multi-Class Active Learning
We present an active learning framework to simultaneously learn appearance and contextual models for scene understanding tasks (multi-class classification). Existing multi-class a...
Behjat Siddiquie, Abhinav Gupta
SDM
2010
SIAM
218views Data Mining» more  SDM 2010»
13 years 6 months ago
Confidence-Based Feature Acquisition to Minimize Training and Test Costs
We present Confidence-based Feature Acquisition (CFA), a novel supervised learning method for acquiring missing feature values when there is missing data at both training and test...
Marie desJardins, James MacGlashan, Kiri L. Wagsta...