Graph Learning with Spectral Connectivity Priors for Scarce Data

arXiv:2609.27278 · cs.LG, eess.SP · Submitted 2026-09-23 · Read on arXiv

cs.LG, eess.SP

Submitted: 2026-09-23

Updated: 2026-09-23

Comments: 5 pages, 1 figure. Submitted to IEEE ICASSP 2027

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

Terminology

• Adjacency Matrix — 6× in this paper · explained in 1 episode
• Sparsity — 6× in this paper · explained in 4 episodes
• Regularization — 5× in this paper · explained in 3 episodes
• Fidelity — 3× in this paper · explained in 2 episodes
• Objective Function — 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
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Hilbert Space — 1× in this paper · explained in 2 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Semidefinite Program (SDP) — 1× in this paper · explained in 2 episodes
• Spectral Gap — 1× in this paper · explained in 5 episodes
• Structural Constraints — 1× in this paper · explained in 2 episodes

Sources

• Sparse Graph Learning from Sparse Data via Fiedler Number Maximization

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