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CORR
2000
Springer
120views Education» more  CORR 2000»
13 years 7 months ago
Scaling Up Inductive Logic Programming by Learning from Interpretations
When comparing inductive logic programming (ILP) and attribute-value learning techniques, there is a trade-off between expressive power and efficiency. Inductive logic programming ...
Hendrik Blockeel, Luc De Raedt, Nico Jacobs, Bart ...
KDD
2007
ACM
197views Data Mining» more  KDD 2007»
14 years 8 months ago
Learning the kernel matrix in discriminant analysis via quadratically constrained quadratic programming
The kernel function plays a central role in kernel methods. In this paper, we consider the automated learning of the kernel matrix over a convex combination of pre-specified kerne...
Jieping Ye, Shuiwang Ji, Jianhui Chen
EUROCOLT
1999
Springer
13 years 12 months ago
Mind Change Complexity of Learning Logic Programs
The present paper motivates the study of mind change complexity for learning minimal models of length-bounded logic programs. It establishes ordinal mind change complexity bounds ...
Sanjay Jain, Arun Sharma
ICML
2002
IEEE
14 years 8 months ago
Learning the Kernel Matrix with Semi-Definite Programming
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...
ISTA
2003
13 years 9 months ago
Reflective Learning in Large Companies - can it work?
: A growing number of universities and companies are now becoming focused on promoting learning that is not merely instrumental. These aspirations refer to deep learning, transform...
Mihaela-Monica Vladoiu, Beatrice Matenciuc-Antones...