Revisiting Weight Drop: Beyond Regularization in Modern Deep Learning
Weight decay and ℓ2 regularization are crucial in machine learning, especially to limit network capacity and reduce irrelevant weight components. ...
Tag: Regularization
HyPO: A hybrid reinforcement learning algorithm that uses offline data for contrast-based preference optimization and unlabeled online data for KL regularization
A fundamental aspect of ai research involves tuning large language models (LLMs) to align their outputs with human preferences. This ...
Understanding Overfitting in ConvNets
Introduction Overfitting in ConvNets is a challenge in deep learning and neural networks, where a model learns too much from ...
WTF is Regularization and what is it for?
“Prevention is better than cure,” goes the old saying, reminding us that it is easier to prevent something from happening ...
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