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ICML
2006
IEEE
14 years 8 months ago
A graphical model for predicting protein molecular function
We present a simple statistical model of molecular function evolution to predict protein function. The model description encodes general knowledge of how molecular function evolve...
Barbara E. Engelhardt, Michael I. Jordan, Steven E...
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...
JMLR
2010
192views more  JMLR 2010»
13 years 2 months ago
Inducing Tree-Substitution Grammars
Inducing a grammar from text has proven to be a notoriously challenging learning task despite decades of research. The primary reason for its difficulty is that in order to induce...
Trevor Cohn, Phil Blunsom, Sharon Goldwater
CGI
2004
IEEE
13 years 11 months ago
BlobTree Trees
In recent years several methods for modeling botanical trees have been proposed. The geometry and topology of tree skeletons can be well described by L-systems; however, there are...
Callum Galbraith, Peter MacMurchy, Brian Wyvill
TSP
2010
13 years 2 months ago
Learning Gaussian tree models: analysis of error exponents and extremal structures
The problem of learning tree-structured Gaussian graphical models from independent and identically distributed (i.i.d.) samples is considered. The influence of the tree structure a...
Vincent Y. F. Tan, Animashree Anandkumar, Alan S. ...