Geometry-Aware Graph Construction via Adaptive Spectral Bandwidth Control

arXiv:2609.03306 · cs.LG, eess.SP · Submitted 2026-09-03 · Read on arXiv

cs.LG, eess.SP

Submitted: 2026-09-03

Updated: 2026-09-03

Terminology

• Intrinsic Dimension — 20× in this paper · explained in 2 episodes
• Accuracy — 10× in this paper · explained in 1 episode
• Self-Supervised Learning — 7× in this paper · explained in 8 episodes
• Embeddings — 6× in this paper · explained in 2 episodes
• Graph Construction — 6× in this paper · explained in 3 episodes
• Adaptation — 5× in this paper · explained in 1 episode
• Clustering — 5× in this paper · explained in 2 episodes
• Spectral clustering — 4× in this paper · explained in 2 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• Contrastive Learning — 2× in this paper · explained in 5 episodes
• Downstream Tasks — 2× in this paper · explained in 2 episodes
• Failure Modes — 2× in this paper · explained in 3 episodes
• Label Propagation — 2× in this paper
• Regularization — 2× in this paper · explained in 3 episodes
• Sparsity — 2× in this paper · explained in 4 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Ambient Dimension — 1× in this paper · explained in 1 episode
• Fidelity — 1× in this paper · explained in 2 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Semi-supervised Learning — 1× in this paper · explained in 4 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes

Sources

• The Geometry of Self-supervised Learning Models and its Impact on Transfer Learning
• Study of Manifold Geometry using Multiscale Non-Negative Kernel Graphs
• Improved Baselines with Momentum Contrastive Learning

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