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» Sparse Optimization for Second Order Kernel Methods
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ECCV
2006
Springer
14 years 10 months ago
Statistical Priors for Efficient Combinatorial Optimization Via Graph Cuts
Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
Daniel Cremers, Leo Grady
JMLR
2010
103views more  JMLR 2010»
13 years 3 months ago
Learning Nonlinear Dynamic Models from Non-sequenced Data
Virtually all methods of learning dynamic systems from data start from the same basic assumption: the learning algorithm will be given a sequence of data generated from the dynami...
Tzu-Kuo Huang, Le Song, Jeff Schneider
BMCBI
2007
143views more  BMCBI 2007»
13 years 8 months ago
Factor analysis for gene regulatory networks and transcription factor activity profiles
Background: Most existing algorithms for the inference of the structure of gene regulatory networks from gene expression data assume that the activity levels of transcription fact...
Iosifina Pournara, Lorenz Wernisch
CIKM
2009
Springer
14 years 3 months ago
Learning to rank graphs for online similar graph search
Many applications in structure matching require the ability to search for graphs that are similar to a query graph, i.e., similarity graph queries. Prior works, especially in chem...
Bingjun Sun, Prasenjit Mitra, C. Lee Giles
JSCIC
2007
125views more  JSCIC 2007»
13 years 8 months ago
Discrete Fundamental Solution Preconditioning for Hyperbolic Systems of PDE
We present a new preconditioner for the iterative solution of linear systems of equations arising from discretizations of systems of first order partial differential equations (P...
Henrik Brandén, Sverker Holmgren, Per Sundq...