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NIPS
2004
14 years 10 months ago
Instance-Specific Bayesian Model Averaging for Classification
Classification algorithms typically induce population-wide models that are trained to perform well on average on expected future instances. We introduce a Bayesian framework for l...
Shyam Visweswaran, Gregory F. Cooper
ACL
2010
14 years 7 months ago
Active Learning-Based Elicitation for Semi-Supervised Word Alignment
Semi-supervised word alignment aims to improve the accuracy of automatic word alignment by incorporating full or partial manual alignments. Motivated by standard active learning q...
Vamshi Ambati, Stephan Vogel, Jaime G. Carbonell
ICDM
2010
IEEE
128views Data Mining» more  ICDM 2010»
14 years 7 months ago
User-Based Active Learning
Active learning has been proven a reliable strategy to reduce manual efforts in training data labeling. Such strategies incorporate the user as oracle: the classifier selects the m...
Christin Seifert, Michael Granitzer
ICASSP
2010
IEEE
14 years 9 months ago
Speech modeling based on committee-based active learning
We propose a committee-based active learning method for large vocabulary continuous speech recognition. In this approach, multiple recognizers are prepared beforehand, and the rec...
Yuzu Hamanaka, Koichi Shinoda, Sadaoki Furui, Tada...
ICIP
2006
IEEE
15 years 11 months ago
Precision-Oriented Active Selection for Interactive Image Retrieval
Active learning methods have been considered with an increased interest in the content-based image retrieval (CBIR) community. Those methods used to be based on classical classifi...
Philippe Henri Gosselin, Matthieu Cord