Logic Nest

Deep Learning

Can Weight Decay Speed Grokking Convergence?

Introduction to Weight Decay and Grokking In the realm of deep learning, two essential concepts that warrant discussion are weight decay and grokking. Weight decay is a regularization technique employed in the training of neural networks. Its primary objective is to prevent overfitting, a scenario where the model learns noise and patterns that are not […]

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Understanding the Impact of Batch Size on Grokking Dynamics

Introduction to Grokking Dynamics Grokking dynamics is a crucial concept in the field of computational learning, particularly when assessing how machine learning models evolve in their performance over time. It encapsulates the processes through which a model develops an understanding of the underlying patterns in data, eventually leading to improved predictive capabilities. The term ‘grok’

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