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» Learning large margin classifiers locally and globally
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CSL
2010
Springer
13 years 7 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...
BMVC
2010
13 years 5 months ago
Implicit Shape Kernel for Discriminative Learning of the Hough Transform Detector
The Hough transform provides an efficient way to detect objects. Various methods have been proposed to achieve discriminative learning of the Hough transform, but they have usuall...
Yimeng Zhang, Tsuhan Chen
CVPR
2010
IEEE
13 years 12 months ago
On the design of robust classifiers for computer vision
The design of robust classifiers, which can contend with the noisy and outlier ridden datasets typical of computer vision, is studied. It is argued that such robustness requires l...
Hamed Masnadi-Shirazi, Nuno Vasconcelos, Vijay Mah...
PUK
2000
13 years 9 months ago
An Accessibility graph learning approach for task planning in large domains
Abstract. In the stream of research that aims to speed up practical planners, we propose a new approach to task planning based on Probabilistic Roadmap Methods (PRM). Our contribut...
Emmanuel Guere, Rachid Alami
ICASSP
2009
IEEE
14 years 2 months ago
Maximizing global entropy reduction for active learning in speech recognition
We propose a new active learning algorithm to address the problem of selecting a limited subset of utterances for transcribing from a large amount of unlabeled utterances so that ...
Balakrishnan Varadarajan, Dong Yu, Li Deng, Alex A...