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A Convex Optimization Framework for Regularized Geodesic Distances
DescriptionWe introduce a general convex optimization problem for computing regularized geodesic distances. We propose three regularizers, analytical solutions for special cases, and efficient optimization algorithms. We generalize the approach to the all pairs case using the product manifold, leading to symmetric distances. Our regularized distances compare favorably to existing methods.
Event Type
Technical Paper
TimeMonday, 7 August 202311:39am - 11:49am PDT
LocationPetree Hall C
Interest Areas
Research & Education
Recordings
Livestreamed
Recorded
Keywords
Modeling
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