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ML
2006
ACM
131views Machine Learning» more  ML 2006»
14 years 10 months ago
Markov logic networks
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...
Matthew Richardson, Pedro Domingos
ICONIP
1998
15 years 5 days ago
A Comparison of Learning Transfer in Networks and Humans
Learning transfer is the improvement in performance on one task having learnt a related task. That the degree of transfer is signi cantly greater in humans than other primates and...
Steven Phillips
ML
2010
ACM
185views Machine Learning» more  ML 2010»
14 years 5 months ago
Learning to rank on graphs
Graph representations of data are increasingly common. Such representations arise in a variety of applications, including computational biology, social network analysis, web applic...
Shivani Agarwal
ICML
1995
IEEE
15 years 11 months ago
Visualizing High-Dimensional Structure with the Incremental Grid Growing Neural Network
Understanding high-dimensional real world data usually requires learning the structure of the data space. The structure maycontain high-dimensional clusters that are related in co...
Justine Blackmore, Risto Miikkulainen
IDA
2008
Springer
14 years 11 months ago
Symbolic methodology for numeric data mining
Currently statistical and artificial neural network methods dominate in data mining applications. Alternative relational (symbolic) data mining methods have shown their effectivene...
Boris Kovalerchuk, Evgenii Vityaev