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Riemannian adaptive stochastic gradient algorithms on matrix manifolds., , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 3262-3271. PMLR, (2019)A Riemannian Approach to Ground Metric Learning for Optimal Transport., , , and . CoRR, (2024)TBM-GAN: Synthetic Document Generation with Degraded Background., , , , and . ICDAR (2), volume 14188 of Lecture Notes in Computer Science, page 366-383. Springer, (2023)Riemannian accelerated gradient methods via extrapolation., , , and . CoRR, (2022)On p-norm Path Following in Multiple Kernel Learning for Non-linear Feature Selection., , and . ICML, volume 32 of JMLR Workshop and Conference Proceedings, page 118-126. JMLR.org, (2014)Submodular framework for structured-sparse optimal transport., , , , and . ICML, OpenReview.net, (2024)MMD-Regularized Unbalanced Optimal Transport., , and . Trans. Mach. Learn. Res., (2024)Revisiting stochastic submodular maximization with cardinality constraint: A bandit perspective., , and . Trans. Mach. Learn. Res., (2024)Generalized hierarchical kernel learning., , and . J. Mach. Learn. Res., (2015)Improved Differentially Private Riemannian Optimization: Fast Sampling and Variance Reduction., , , and . Trans. Mach. Learn. Res., (2023)