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» Heterogeneous reasoning in learning to model
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NIPS
2003
13 years 9 months ago
Wormholes Improve Contrastive Divergence
In models that define probabilities via energies, maximum likelihood learning typically involves using Markov Chain Monte Carlo to sample from the model’s distribution. If the ...
Geoffrey E. Hinton, Max Welling, Andriy Mnih
VLDB
2005
ACM
139views Database» more  VLDB 2005»
14 years 1 months ago
Statistical Learning Techniques for Costing XML Queries
Developing cost models for query optimization is significantly harder for XML queries than for traditional relational queries. The reason is that XML query operators are much mor...
Ning Zhang 0002, Peter J. Haas, Vanja Josifovski, ...
COLT
1994
Springer
13 years 11 months ago
Bayesian Inductive Logic Programming
Inductive Logic Programming (ILP) involves the construction of first-order definite clause theories from examples and background knowledge. Unlike both traditional Machine Learnin...
Stephen Muggleton
AMS
2007
Springer
247views Robotics» more  AMS 2007»
14 years 1 months ago
Towards Machine Learning of Motor Skills
Autonomous robots that can adapt to novel situations has been a long standing vision of robotics, artificial intelligence, and cognitive sciences. Early approaches to this goal du...
Jan Peters, Stefan Schaal, Bernhard Schölkopf
CBMS
2008
IEEE
13 years 9 months ago
Effectiveness of Local Feature Selection in Ensemble Learning for Prediction of Antimicrobial Resistance
In the real world concepts are often not stable but change over time. A typical example of this in the biomedical context is antibiotic resistance, where pathogen sensitivity may ...
Seppo Puuronen, Mykola Pechenizkiy, Alexey Tsymbal