Comparison of Second Order Optimization Algorithms in Neural Networks Applied on Large-Scale Problems
This bachelor thesis compares the second order optimization algorithms K-FAC and L-BFGS to common ones of firstorder, Gradient Descent, Stochastic Gradient Descent, and Adam, applied on neural networks for image classification. Networks with different architecture and number of parameters have been...
| Main Authors: | , |
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| Format: | Others |
| Language: | English |
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KTH, Skolan för teknikvetenskap (SCI)
2020
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| Subjects: | |
| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-275721 |