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AGI
2008
13 years 9 months ago
VARIAC: an Autogenous Cognitive Architecture
Learning theory and programs to date are inductively bounded: they can be described as "wind-up toys" which can only learn the kinds of things that their designers envisi...
J. Storrs Hall
ICML
2007
IEEE
14 years 8 months ago
Discriminant kernel and regularization parameter learning via semidefinite programming
Regularized Kernel Discriminant Analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. The performance of RKDA depends on the selection o...
Jieping Ye, Jianhui Chen, Shuiwang Ji
ICML
1998
IEEE
14 years 8 months ago
Genetic Programming and Deductive-Inductive Learning: A Multi-Strategy Approach
Genetic Programming (GP) is a machine learning technique that was not conceived to use domain knowledge for generating new candidate solutions. It has been shown that GP can bene ...
Ricardo Aler, Daniel Borrajo, Pedro Isasi
ACSAC
2003
IEEE
14 years 1 months ago
A Failure to Learn from the Past
On the evening of 2 November 1988, someone “infected” the Internet with a worm program. That program exploited flaws in utility programs in systems based on BSD-derived versi...
Eugene H. Spafford
NIPS
2003
13 years 9 months ago
Multiple-Instance Learning via Disjunctive Programming Boosting
Learning from ambiguous training data is highly relevant in many applications. We present a new learning algorithm for classification problems where labels are associated with se...
Stuart Andrews, Thomas Hofmann