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ICML
2010
IEEE
13 years 10 months ago
Learning Markov Logic Networks Using Structural Motifs
Markov logic networks (MLNs) use firstorder formulas to define features of Markov networks. Current MLN structure learners can only learn short clauses (4-5 literals) due to extre...
Stanley Kok, Pedro Domingos
JMLR
2010
134views more  JMLR 2010»
13 years 3 months ago
Estimation of a Structural Vector Autoregression Model Using Non-Gaussianity
Analysis of causal effects between continuous-valued variables typically uses either autoregressive models or structural equation models with instantaneous effects. Estimation of ...
Aapo Hyvärinen, Kun Zhang, Shohei Shimizu, Pa...
PAKDD
2011
ACM
253views Data Mining» more  PAKDD 2011»
12 years 12 months ago
Balance Support Vector Machines Locally Using the Structural Similarity Kernel
A structural similarity kernel is presented in this paper for SVM learning, especially for learning with imbalanced datasets. Kernels in SVM are usually pairwise, comparing the sim...
Jianxin Wu
BMCBI
2011
13 years 3 months ago
Multithreaded comparative RNA secondary structure prediction using stochastic context-free grammars
Background: The prediction of the structure of large RNAs remains a particular challenge in bioinformatics, due to the computational complexity and low levels of accuracy of state...
Zsuzsanna Sukosd, Bjarne Knudsen, Morten Vaerum, J...
DATAMINE
2006
83views more  DATAMINE 2006»
13 years 9 months ago
Structural Hidden Markov Models Using a Relation of Equivalence: Application to Automotive Designs
Standard hidden Markov models (HMM's) have been studied extensively in the last two decades. It is well known that these models assume state conditional independence of the ob...
Djamel Bouchaffra, Jun Tan