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FUIN
2002
108views more  FUIN 2002»
13 years 4 months ago
Approximate Entropy Reducts
We use information entropy measure to extend the rough set based notion of a reduct. We introduce the Approximate Entropy Reduction Principle (AERP). It states that any simplificat...
Dominik Slezak
ICASSP
2009
IEEE
13 years 11 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...
CSL
2010
Springer
13 years 4 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...
TFS
2008
109views more  TFS 2008»
13 years 3 months ago
Comments on "Fuzzy Probabilistic Approximation Spaces and Their Information Measures"
Some errors in our original paper in defining relative reduct with information measures are pointed out in this paper. It is shown that in our original work, Theorems 10 and 19 hol...
Qinghua Hu, Zongxia Xie, Daren Yu
DSN
2011
IEEE
12 years 4 months ago
Approximate analysis of blocking queueing networks with temporal dependence
—In this paper we extend the class of MAP queueing networks to include blocking models, which are useful to describe the performance of service instances which have a limited con...
Vittoria de Nitto Persone, Giuliano Casale, Evgeni...