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CORR
2010
Springer
130views Education» more  CORR 2010»
15 years 6 months ago
Approximated Structured Prediction for Learning Large Scale Graphical Models
In this paper we propose an approximated structured prediction framework for large scale graphical models and derive message-passing algorithms for learning their parameters effic...
Tamir Hazan, Raquel Urtasun
CVPR
2007
IEEE
16 years 7 months ago
Integrating Global and Local Structures: A Least Squares Framework for Dimensionality Reduction
Linear Discriminant Analysis (LDA) is a popular statistical approach for dimensionality reduction. LDA captures the global geometric structure of the data by simultaneously maximi...
Jianhui Chen, Jieping Ye, Qi Li
BMCBI
2007
168views more  BMCBI 2007»
15 years 6 months ago
Benchmarking consensus model quality assessment for protein fold recognition
Background: Selecting the highest quality 3D model of a protein structure from a number of alternatives remains an important challenge in the field of structural bioinformatics. M...
Liam J. McGuffin
BMCBI
2005
198views more  BMCBI 2005»
15 years 5 months ago
Clustering protein sequences with a novel metric transformed from sequence similarity scores and sequence alignments with neural
Background: The sequencing of the human genome has enabled us to access a comprehensive list of genes (both experimental and predicted) for further analysis. While a majority of t...
Qicheng Ma, Gung-Wei Chirn, Richard Cai, Joseph D....
ESANN
2008
15 years 7 months ago
Using graph-theoretic measures to predict the performance of associative memory models
We test a selection of associative memory models built with different connection strategies, exploring the relationship between the structural properties of each network and its pa...
Lee Calcraft, Rod Adams, Weiliang Chen, Neil Davey