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» Learning Evaluation Functions for Large Acyclic Domains
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BMCBI
2007
116views more  BMCBI 2007»
13 years 8 months ago
Clustering protein environments for function prediction: finding PROSITE motifs in 3D
Background: Structural genomics initiatives are producing increasing numbers of threedimensional (3D) structures for which there is little functional information. Structure-based ...
Sungroh Yoon, Jessica C. Ebert, Eui-Young Chung, G...
SIAMIS
2010
378views more  SIAMIS 2010»
13 years 3 months ago
Global Interactions in Random Field Models: A Potential Function Ensuring Connectedness
Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to ...
Sebastian Nowozin, Christoph H. Lampert
ICML
2004
IEEE
14 years 9 months ago
Relational sequential inference with reliable observations
We present a trainable sequential-inference technique for processes with large state and observation spaces and relational structure. Our method assumes "reliable observation...
Alan Fern, Robert Givan
ICML
2006
IEEE
14 years 9 months ago
Practical solutions to the problem of diagonal dominance in kernel document clustering
In supervised kernel methods, it has been observed that the performance of the SVM classifier is poor in cases where the diagonal entries of the Gram matrix are large relative to ...
Derek Greene, Padraig Cunningham
BMCBI
2006
164views more  BMCBI 2006»
13 years 8 months ago
Evaluation of clustering algorithms for gene expression data
Background: Cluster analysis is an integral part of high dimensional data analysis. In the context of large scale gene expression data, a filtered set of genes are grouped togethe...
Susmita Datta, Somnath Datta