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TSP
2010
13 years 3 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. ...
AUSAI
2008
Springer
13 years 10 months ago
Learning a Generative Model for Structural Representations
Abstract. Graph-based representations have been used with considercess in computer vision in the abstraction and recognition of object shape and scene structure. Despite this, the ...
Andrea Torsello, David L. Dowe
ICPP
2008
IEEE
14 years 3 months ago
Parallelization and Characterization of Probabilistic Latent Semantic Analysis
Probabilistic Latent Semantic Analysis (PLSA) is one of the most popular statistical techniques for the analysis of two-model and co-occurrence data. It has applications in inform...
Chuntao Hong, Wenguang Chen, Weimin Zheng, Jiulong...
IJAR
2010
130views more  IJAR 2010»
13 years 7 months ago
Learning locally minimax optimal Bayesian networks
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Tomi Silander, Teemu Roos, Petri Myllymäki
EUROCRYPT
2006
Springer
14 years 13 days ago
Learning a Parallelepiped: Cryptanalysis of GGH and NTRU Signatures
Abstract. Lattice-based signature schemes following the GoldreichGoldwasser-Halevi (GGH) design have the unusual property that each signature leaks information on the signer's...
Phong Q. Nguyen, Oded Regev