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Normalization Techniques for Training Very Deep Neural Networks
How can we efficiently train very deep neural network architectures? What are the best in-layer normalization options? Read on and find out.
normalization batch-normalization layer-normalization group-normalization
Look inside the workings of "Label Smoothing"
This blog post describes how and why does "trick" of label smoothing improves the model accuracy and when should we use it
deep-learning classification image-classification computer-vision
On the training dynamics of deep networks with L2 regularization
Role of L2 regularization in deep learning, and uncover simple relations between the performance of the model, the L2 coefficient, the learning rate, etc.
regularization l2 learning-rates l2-coefficient
Optimize Ridge Regression Regularizers
Use an optimizer to efficiently find the parameters that maximize ridge regression's performance on a leave-one-out or generalized cross-validation
linear-regression ridge-regression cross-validation regularization
Semixup: In- and Out-of-Manifold Regularization
Semixup is a semi-supervised learning method based on in/out-of-manifold regularization.
semi-supervised-learning manifold-regularization kl-divergence medical-imaging
Regularization in Machine Learning
This article will focus on a technique that helps in avoiding overfitting and also increasing model interpretability.
regularization linear-regression regression article
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