activity
20222026
most citedInductive biases of multi-task learning and finetuning: multiple regimes of feature reuse

2 citations · 2 across the 7 of their papers we have counts for

collaborators
Showing 2026Show all

2 papers · 1 filter

cs.LG2026

A mathematical theory of balancing relational generalization and memorization

Luke Cheng, Samuel Lippl

Humans, animals, and modern machine learning models exhibit impressive abilities to learn complex behaviors and generalize these behaviors to unseen situations. This ability requir…

cs.LG2026

A Theory of How Pretraining Shapes Inductive Bias in Fine-Tuning

Nicolas Anguita, Francesco Locatello, Andrew M. Saxe +4

Pretraining and fine-tuning are central stages in modern machine learning systems. In practice, feature learning plays an important role across both stages: deep neural networks le…