8 citations · 32 across the 13 of their papers we have counts for
5 papers · 1 filter
Semi-Riemannian Manifold Optimization
Tingran Gao, Lek-Heng Lim, Ke Ye
We introduce in this paper a manifold optimization framework that utilizes semi-Riemannian structures on the underlying smooth manifolds. Unlike in Riemannian geometry, where each…
Wasserstein Soft Label Propagation on Hypergraphs: Algorithm and Generalization Error Bounds
Tingran Gao, Shahab Asoodeh, Yi Huang +1
Inspired by recent interests of developing machine learning and data mining algorithms on hypergraphs, we investigate in this paper the semi-supervised learning algorithm of propag…
Gaussian Process Landmarking for Three-Dimensional Geometric Morphometrics
Tingran Gao, Shahar Z. Kovalsky, Doug M. Boyer +1
We demonstrate applications of the Gaussian process-based landmarking algorithm proposed in [T. Gao, S.Z. Kovalsky, and I. Daubechies, SIAM Journal on Mathematics of Data Science (…
Curvature of Hypergraphs via Multi-Marginal Optimal Transport
Shahab Asoodeh, Tingran Gao, James Evans
We introduce a novel definition of curvature for hypergraphs, a natural generalization of graphs, by introducing a multi-marginal optimal transport problem for a naturally defined…
Gaussian Process Landmarking on Manifolds
Tingran Gao, Shahar Z. Kovalsky, Ingrid Daubechies
As a means of improving analysis of biological shapes, we propose an algorithm for sampling a Riemannian manifold by sequentially selecting points with maximum uncertainty under a…