1 citations · 1 across the 7 of their papers we have counts for
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How are linear representations learned? Exact solutions to the dynamics of abstraction
William W. Yang, Andrew M. Saxe, Peter E. Latham
In artificial and biological neural networks, concepts are often encoded as consistent linear directions in representation space. In deep learning, this idea is known as the linear…
Optimal Representation Size: High-Dimensional Analysis of Pretraining and Linear Probing
Valentina Njaradi, Clémentine Dominé, Rachel Swanson +2
Learning to generalise from limited data is a fundamental challenge for both artificial and biological systems. A common strategy is to extract reusable structure from abundant unl…
Optimal Learning Rate Schedule for Balancing Effort and Performance
Valentina Njaradi, Rodrigo Carrasco-Davis, Peter E. Latham +1
Learning how to learn efficiently is a fundamental challenge for biological agents and a growing concern for artificial ones. To learn effectively, an agent must regulate its learn…