Revisiting the Volume Hypothesis

arXiv:2606.31282 · cs.LG · Submitted 2026-06-30 · Read on arXiv

cs.LG

Submitted: 2026-06-30

Updated: 2026-09-27

Terminology

• Generalization — 65× in this paper · explained in 13 episodes
• Accuracy — 29× in this paper · explained in 1 episode
• Regularization — 4× in this paper · explained in 3 episodes
• Stochastic Gradient Descent (SGD) — 3× in this paper · explained in 5 episodes
• Generalization Bounds — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Generalizability — 1× in this paper · explained in 6 episodes
• Hierarchical Framework — 1× in this paper · explained in 2 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• VC Dimension — 1× in this paper · explained in 2 episodes

Sources

• Do Neural Networks Need Gradient Descent to Generalize? A Theoretical Study
• Sharp Minima Can Generalize: A Loss Landscape Perspective On Data
• Deep Learning Scaling is Predictable, Empirically
• Estimating the Probability of Sampling a Trained Neural Network at Random

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