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JMLR
2010
202views more  JMLR 2010»
14 years 11 months ago
Learning the Structure of Deep Sparse Graphical Models
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
BMCBI
2007
135views more  BMCBI 2007»
15 years 4 months ago
Sequence similarity is more relevant than species specificity in probabilistic backtranslation
Background: Backtranslation is the process of decoding a sequence of amino acids into the corresponding codons. All synthetic gene design systems include a backtranslation module....
Alfredo Ferro, Rosalba Giugno, Giuseppe Pigola, Al...
ICIP
2003
IEEE
16 years 6 months ago
Stochastic attributed K-d tree modeling of technical paper title pages
Structural information about a document is essential for structured query processing, indexing, and retrieval. A document page can be partitioned into a hierarchy of homogeneous r...
Song Mao, Azriel Rosenfeld, Tapas Kanungo
ICASSP
2009
IEEE
15 years 8 months ago
Graphical Models: Statistical inference vs. determination
Using discrete Hidden-Markov-Models (HMMs) for recognition requires the quantization of the continuous feature vectors. In handwritten whiteboard note recognition it turns out tha...
Joachim Schenk, Benedikt Hörnler, Artur Braun...
ICIP
2002
IEEE
16 years 6 months ago
A study of contextual modeling and texture characterization for multiscale Bayesian segmentation
In this paper, we demonstrate that multiscale Bayesian image segmentation can be enhanced by improving both contextual modeling and statistical texture characterization. Firstly, ...
Guoliang Fan, Xiaomu Song