Partial Optimal Transport on the Circle for All Transported Masses in O(N log N)

arXiv:2608.23910 · cs.LG, cs.DS · Submitted 2026-08-24 · Read on arXiv

cs.LG, cs.DS

Submitted: 2026-08-24

Updated: 2026-08-24

Code: https://github.com/mint-vu/Partial_Wasserstein_on_Circles

Terminology

• Optimal Transport — 17× in this paper · explained in 5 episodes
• Accuracy — 9× in this paper · explained in 1 episode
• Benchmark — 3× in this paper · explained in 2 episodes
• Stiefel manifold — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Failure Modes — 2× in this paper · explained in 3 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Alternation — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Degeneracy — 1× in this paper · explained in 3 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Optimal Transport (OT) — 1× in this paper · explained in 4 episodes
• Sample Complexity — 1× in this paper · explained in 15 episodes
• Systematic Bias — 1× in this paper · explained in 3 episodes
• Wasserstein Distance — 1× in this paper · explained in 4 episodes

Sources

• A Grassmann Manifold Handbook: Basic Geometry and Computational Aspects

Related papers

• Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
• AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
• Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
• Convergence issues in Relational Concept Analysis based on AOC-posets
• Beliefs Beyond Posteriors: Local-Consistency Optimisation for Bayesian Neural Networks
• Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks