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# Discovering Neural Nets with Low Kolmogorov Complexity and High Generalization Capability

@inproceedings{SchmidhuberIDSIA1997DiscoveringNN, title={Discovering Neural Nets with Low Kolmogorov Complexity and High Generalization Capability}, author={urgen SchmidhuberIDSIA and Corso Elvezia}, year={1997} }

- Published 1997

Many neural net learning algorithms aim at nding \simple" nets to explain training data. The expectation is: the \simpler" the networks, the better the generalization on test data (! Occam's razor). Previous implementations, however, use measures for \simplicity" that lack the power, universality and elegance of those based on Kolmogorov complexity and Solomonoo's algorithmic probability. Likewise, most previous approaches (especially those of the \Bayesian" kind) suuer from the problem ofâ€¦Â CONTINUE READING

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