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ICASSP
2011
IEEE
12 years 11 months ago
Multi-view and multi-objective semi-supervised learning for large vocabulary continuous speech recognition
Current hidden Markov acoustic modeling for large vocabulary continuous speech recognition (LVCSR) relies on the availability of abundant labeled transcriptions. Given that speech...
Xiaodong Cui, Jing Huang, Jen-Tzung Chien
NIPS
2007
13 years 9 months ago
Loop Series and Bethe Variational Bounds in Attractive Graphical Models
Variational methods are frequently used to approximate or bound the partition or likelihood function of a Markov random field. Methods based on mean field theory are guaranteed ...
Erik B. Sudderth, Martin J. Wainwright, Alan S. Wi...
CVPR
2009
IEEE
15 years 2 months ago
Higher-Order Clique Reduction in Binary Graph Cut
We introduce a new technique that can reduce any higher-order Markov random field with binary labels into a first-order one that has the same minima as the original. Moreover, w...
Hiroshi Ishikawa 0002
ACL
2009
13 years 5 months ago
Do Automatic Annotation Techniques Have Any Impact on Supervised Complex Question Answering?
In this paper, we analyze the impact of different automatic annotation methods on the performance of supervised approaches to the complex question answering problem (defined in th...
Yllias Chali, Sadid A. Hasan, Shafiq R. Joty
CVPR
2008
IEEE
14 years 9 months ago
Who killed the directed model?
Prior distributions are useful for robust low-level vision, and undirected models (e.g. Markov Random Fields) have become a central tool for this purpose. Though sometimes these p...
Justin Domke, Alap Karapurkar, Yiannis Aloimonos