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» A Theory for Memory-Based Learning
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NIPS
2000
15 years 6 months ago
Learning Continuous Distributions: Simulations With Field Theoretic Priors
Learning of a smooth but nonparametric probability density can be regularized using methods of Quantum Field Theory. We implement a field theoretic prior numerically, test its eff...
Ilya Nemenman, William Bialek
IJON
2007
184views more  IJON 2007»
15 years 5 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
KCAP
2011
ACM
14 years 8 months ago
Eliciting hierarchical structures from enumerative structures for ontology learning
Some discourse structures such as enumerative structures have typographical, punctuational and laying out characteristics which (1) make them easily identifiable and (2) convey hi...
Mouna Kamel, Bernard Rothenburger
154
Voted
COLT
1993
Springer
15 years 9 months ago
Parameterized Learning Complexity
We describe three applications in computational learning theory of techniques and ideas recently introduced in the study of parameterized computational complexity. (1) Using param...
Rodney G. Downey, Patricia A. Evans, Michael R. Fe...
TEI
2012
ACM
257views Hardware» more  TEI 2012»
14 years 18 days ago
Beyond affordance: tangibles' hybrid nature
A prevalent assumption behind interface approaches that employ physical means of interaction is that this leverages users’ prior knowledge from the real world. This paper scruti...
Eva Hornecker