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4min chapter
[19] Dumitru Erhan - Understanding Deep Architectures and the Effect of Unsupervised Pretraining
The Thesis Review
Exploring Regularization Hypotheses in Deep Learning Experiments
This chapter investigates three key hypotheses — conditioning, optimization, and regularization — related to deep architectures. The primary focus is on the regularization hypothesis, exploring experimental methodologies and the iterative nature of scientific experimentation in this domain.
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