SOURCE-LINKED INTELLIGENCE

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

arXiv · AI, language, vision and robotics · article · Aug 24, 2026 · UTC

Partial optimal transport compares two measures while leaving part of the mass unmatched, which is what makes it robust to outliers, occlusion, and clutter. The quantity of interest is usually the whole profile - the optimal cost at every transported cardinality - because the right amount to transport is rarely known in advance, and on the real line the PAWL algorithm returns that profile in $O(N\log N)$. Much data is periodic rather than linear: angles, phases, orientations, time of day, hue, and every direction obtained by projecting onto a great circle. On the circle the same problem acquir

Read original source ↗ Open in workspace

recordType

paper

region

Global