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ADCM
2008
136views more  ADCM 2008»
14 years 11 months ago
Learning and approximation by Gaussians on Riemannian manifolds
Learning function relations or understanding structures of data lying in manifolds embedded in huge dimensional Euclidean spaces is an important topic in learning theory. In this ...
Gui-Bo Ye, Ding-Xuan Zhou
COGSCI
2010
105views more  COGSCI 2010»
14 years 11 months ago
The Role of Explanation in Discovery and Generalization: Evidence From Category Learning
Research in education and cognitive development suggests that explaining plays a key role in learning and generalization: When learners provide explanations--even to themselves--t...
Joseph J. Williams, Tania Lombrozo
DM
2010
102views more  DM 2010»
14 years 11 months ago
Covering graphs with matchings of fixed size
Let m be a positive integer and let G be a graph. We consider the question: can the edge set E(G) of G be expressed as the union of a set M of matchings of G each of which has siz...
David Cariolaro, Hung-Lin Fu
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
IJON
2007
81views more  IJON 2007»
14 years 10 months ago
Statistical analysis of spatially embedded networks: From grid to random node positions
Many conceptual studies of local cortical networks assume completely random wiring. For spatially extended networks, however, such random graph models are inadequate. The geometry...
Nicole Voges, Ad Aertsen, Stefan Rotter