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» Learning and using relational theories
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IJON
2007
184views more  IJON 2007»
15 years 6 months ago
Convex incremental extreme learning machine
Unlike the conventional neural network theories and implementations, Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden n...
Guang-Bin Huang, Lei Chen
ECML
2007
Springer
16 years 23 days ago
Exploiting Term, Predicate, and Feature Taxonomies in Propositionalization and Propositional Rule Learning
Knowledge representations using semantic web technologies often provide information which translates to explicit term and predicate taxonomies in relational learning. We show how t...
Monika Záková, Filip Zelezný
RSKT
2009
Springer
16 years 1 months ago
Learning Optimal Parameters in Decision-Theoretic Rough Sets
A game-theoretic approach for learning optimal parameter values for probabilistic rough set regions is presented. The parameters can be used to define approximation regions in a p...
Joseph P. Herbert, Jingtao Yao
ICCV
2011
IEEE
14 years 6 months ago
Learning Spatiotemporal Graphs of Human Activities
Complex human activities occurring in videos can be defined in terms of temporal configurations of primitive actions. Prior work typically hand-picks the primitives, their total...
William Brendel, Sinisa Todorovic
ICML
2009
IEEE
16 years 7 months ago
Archipelago: nonparametric Bayesian semi-supervised learning
Semi-supervised learning (SSL), is classification where additional unlabeled data can be used to improve accuracy. Generative approaches are appealing in this situation, as a mode...
Ryan Prescott Adams, Zoubin Ghahramani