AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Despite the widespread use of Low-Rank Adaptation (LoRA), little is known about its dynamics in continual learning and the mechanisms by which low-rank updates affect catastrophic forgetting. We provide an asymptotically exact dynamical characterization of LoRA in a solvable two-task teacher-student model. In the high-...
Auxiliary learning is an optimization paradigm in which a neural network's performance on a target task is improved by jointly training it on additional tasks. However, the mechanisms behind this improvement remain poorly understood. We study this problem using a teacher-student framework and derive a closed system of...
This work cast neuron selection as the problem of coarse-graining the hidden layer by retaining a subset of its neurons, and scores each putative selection by the mapping entropy (ME), measuring the loss of discriminatory power inherent in discarding part of the network neurons.
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