Web Reference: In ML research, "grokking" is not used as a synonym for "generalization"; rather, it names a sometimes-observed delayed‑generalization training phenomenon in which training and held‑out performance do not improve in tandem, and in which held‑out performance rises abruptly later. Jan 6, 2022 · In this paper we propose to study generalization of neural networks on small algorithmically generated datasets. In this setting, questions about data efficiency, memorization, generalization, and speed of learning can be studied in great detail. Grokking refers to a fascinating phenomenon in deep learning where a neural network, after training for a significantly extended period—often long after it appears to have overfitted the training data—suddenly experiences a sharp improvement in validation accuracy.
YouTube Excerpt: Grokking Asynchronous Work in Node
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