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ICML
2000
IEEE
14 years 8 months ago
Meta-Learning by Landmarking Various Learning Algorithms
Landmarking is a novel approach to describing tasks in meta-learning. Previous approaches to meta-learning mostly considered only statistics-inspired measures of the data as a sou...
Bernhard Pfahringer, Hilan Bensusan, Christophe G....
IJCAI
2007
13 years 9 months ago
Effective Control Knowledge Transfer through Learning Skill and Representation Hierarchies
Learning capabilities of computer systems still lag far behind biological systems. One of the reasons can be seen in the inefficient re-use of control knowledge acquired over the...
Mehran Asadi, Manfred Huber
ICCBR
2005
Springer
14 years 1 months ago
Selecting the Best Units in a Fleet: Performance Prediction from Equipment Peers
We focus on the problem of selecting the few vehicles in a fleet that are expected to last the longest without failure. The prediction of each vehicle’s remaining life is based o...
Anil Varma, Kareem S. Aggour, Piero P. Bonissone
MLDM
2001
Springer
14 years 5 days ago
Learning XML Grammars
0 Temporal Abstractions and Case-Based Reasoning for Medical Course Data: Two Prognostic Applications R. Schmidt and R. Gierl University of Rostock, Germany 9.00-9.30 Local Learnin...
Henning Fernau
ATAL
2007
Springer
14 years 1 months ago
A framework for agent-based distributed machine learning and data mining
This paper proposes a framework for agent-based distributed machine learning and data mining based on (i) the exchange of meta-level descriptions of individual learning processes ...
Jan Tozicka, Michael Rovatsos, Michal Pechoucek