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» Using Random Forests in the Structured Language Model
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ICPR
2008
IEEE
14 years 3 months ago
Face super-resolution using 8-connected Markov Random Fields with embedded prior
In patch based face super-resolution method, the patch size is usually very small, and neighbor patches’ relationship via overlapped regions is only to keep smoothness of recons...
Kai Guo, Xiaokang Yang, Rui Zhang, Guangtao Zhai, ...
SIGIR
2009
ACM
14 years 3 months ago
Extracting structured information from user queries with semi-supervised conditional random fields
When search is against structured documents, it is beneficial to extract information from user queries in a format that is consistent with the backend data structure. As one step...
Xiao Li, Ye-Yi Wang, Alex Acero
ENVSOFT
2006
125views more  ENVSOFT 2006»
13 years 8 months ago
Sensitivity analysis based on regional splits and regression trees (SARS-RT)
A global sensitivity analysis with regional properties is introduced. This method is demonstrated on two synthetic and one hydraulic example. It can be shown that an uncertainty a...
Florian Pappenberger, Ion Iorgulescu, Keith J. Bev...
CAISE
2003
Springer
14 years 1 months ago
Modelling Telecare Service Requirements for Older People Using the Unified Modelling Language
Providing technology support for older people offers distinct challenges for social and IT systems delivery. The definition and integration of services, the diversity of supply, va...
Ken Lunn, Andrew Sixsmith, Ann Lindsay, Marja Vaar...
ICASSP
2011
IEEE
13 years 9 days ago
Deep Belief Networks using discriminative features for phone recognition
Deep Belief Networks (DBNs) are multi-layer generative models. They can be trained to model windows of coefficients extracted from speech and they discover multiple layers of fea...
Abdel-rahman Mohamed, Tara N. Sainath, George Dahl...