Essays about: "Regularization Strength Synthetic Data Generation"

Found 2 essays containing the words Regularization Strength Synthetic Data Generation.

1. 1. Investigating Relations between Regularization and Weight Initialization in Artificial Neural Networks

   University essay from Lunds universitet/Beräkningsbiologi och biologisk fysik - Genomgår omorganisation

   Author : Rasmus Sjöö; [2022]
   Keywords : Artificial Neural Networks; L1 Regularization; L2 Regularization; Loss Function; Maximum Likelihood; Regularization Strength Synthetic Data Generation; Weight Initialization; Physics and Astronomy;

   Abstract : L2 regularization is a common method used to prevent overtraining in artificial neural networks. However, an issue with this method is that the regularization strength has to be properly adjusted for it to work as intended. This value is usually found by trial and error which can take some time, especially for larger networks. READ MORE

3. 2. Prediction of appropriate L2 regularization strengths through Bayesian formalism

   University essay from Lunds universitet/Beräkningsbiologi och biologisk fysik - Genomgår omorganisation; Lunds universitet/Institutionen för astronomi och teoretisk fysik - Genomgår omorganisation

   Author : Alexander Degener; [2022]
   Keywords : Machine learning; Artificial Neural Network; L2 regularization strength; Bayesian formalism; Classification tasks; Physics and Astronomy;

   Abstract : This paper proposes and investigates a Bayesian relation between optimal L2 regularization strengths and the number of training patterns and hidden nodes used for an artificial neural network. The results support the proposed dependence for number of training patterns, while the dependence on hidden architecture was less clear. READ MORE