
The author explores implicit regularization effects in multi-task learning and fine-tuning, highlighting biases towards feature sharing and sparse task-specific feature learning. The study uncovers a novel nested feature selection regime that enhances performance through sparsity.


coremsg

implicit-regularization-effects-in-multi-task-learning-and-fine-tuning-of-overparameterized-neural-networks


Implicit Regularization Effects in Multi-Task Learning and Fine-Tuning of Overparameterized Neural Networks
