“A Convex Optimization Framework for Regularized Geodesic Distances” by Edelstein, Guillen, Solomon and Ben-Chen

  • ©Michal Edelstein, Nestor Guillen, Justin M. Solomon, and Mirela (Miri) Ben-Chen

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Title:

    A Convex Optimization Framework for Regularized Geodesic Distances

Session/Category Title: Geometric Optimization


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Abstract:


    We 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.


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