An Analysis of Single-Layer Networks in Unsupervised Feature Learning

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Summary

The results show that large numbers of hidden nodes and dense feature extraction are critical to achieving high performance—so critical, in fact, that when these parameters are pushed to their limits, they achieve state-of-the-art performance on both CIFAR-10 and NORB using only a single layer of features.

Type
article
Published
2011-12-01
Cited by
4,557
References
36

Keywords

Computer science, Hyperparameter, Cluster analysis, Artificial intelligence, Feature (linguistics)

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