Informational Frustration in Neural Manifolds: Shannon Bottlenecks and the Limits of Learnability

arXiv:2606.30512 · cs.LG, cs.AI, cs.CC, cs.CG, stat.ML · Submitted 2026-06-29 · Read on arXiv

Srinivasa Rao P., Vangmayi P Reddy

cs.LG, cs.AI, cs.CC, cs.CG, stat.ML

Submitted: 2026-06-29

Comments: 8

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Frustration — 13× in this paper · explained in 3 episodes
• von Neumann Entropy — 12× in this paper · explained in 2 episodes
• Entropic Learnability Horizon — 11× in this paper
• Grokking — 9× in this paper · explained in 2 episodes
• Generalization — 8× in this paper · explained in 14 episodes
• Memorization — 7× in this paper · explained in 4 episodes
• Entropic Gradient Descent — 5× in this paper
• Phase Transition — 5× in this paper · explained in 3 episodes
• Overfitting — 4× in this paper · explained in 2 episodes
• Mutual Information — 3× in this paper · explained in 2 episodes
• Information Bottleneck — 2× in this paper · explained in 3 episodes
• Unified Framework — 2× in this paper · explained in 6 episodes
• Absorb — 1× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Epistemic Uncertainty — 1× in this paper · explained in 12 episodes
• Generalization Bounds — 1× in this paper · explained in 2 episodes
• Hilbert Space — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Phase Transitions — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Stochastic Gradient Descent — 1× in this paper
• Stochastic Gradient Descent (SGD) — 1× in this paper · explained in 5 episodes
• VC Dimension — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• GenLabel: Mixup Relabeling using Generative Models

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