Exact Rank-Space KL Projection for Shared-Marginal Low-Rank Factors: Application to Doubly Stochastic Clustering

arXiv:2608.08642 · cs.LG, math.OC · Submitted 2026-08-09 · Read on arXiv

Enliang Hu

cs.LG, math.OC

Submitted: 2026-08-09

Updated: 2026-08-11

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

Terminology

• Clustering — 49× in this paper · explained in 2 episodes
• Optimal Transport — 8× in this paper · explained in 5 episodes
• Regularization — 8× in this paper · explained in 3 episodes
• Spectral Clustering — 7× in this paper · explained in 3 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Decoder — 5× in this paper · explained in 2 episodes
• Graph Construction — 5× in this paper · explained in 3 episodes
• Ablation — 4× in this paper · explained in 1 episode
• AUC — 3× in this paper · explained in 2 episodes
• Benchmark — 3× in this paper · explained in 2 episodes
• Gauge Fixing — 2× in this paper · explained in 2 episodes
• Nyström Method — 2× in this paper · explained in 2 episodes
• Ablation Study — 1× in this paper · explained in 3 episodes
• Evaluation Protocol — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Fixed Point — 1× in this paper · explained in 2 episodes
• Intermediate Regime — 1× in this paper · explained in 2 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Parameterization — 1× in this paper · explained in 2 episodes
• Semi-supervised Learning — 1× in this paper · explained in 4 episodes
• Sparsity — 1× in this paper · explained in 5 episodes
• Structural Control — 1× in this paper · explained in 2 episodes

Sources

• A Riemannian Approach to Low-Rank Optimal Transport

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