riemannian gradient descent

Fast Non-convex Matrix Sensing with Optimal Sample Complexity UAI 2025 Convergence and Complexity Guarantee for Inexact First-order Riemannian Optimization Algorithms ICML 2024 Convergence and Trade-Offs in Riemannian Gradient Descent and Riemannian Proximal Point ICML 2024 Manifold Learning by Mixture Models of VAEs for Inverse Problems JMLR 2024 Quantitative Convergences of Lie Group Momentum Optimizers NeurIPS 2024 Horospherical Decision Boundaries for Large Margin Classification in Hyperbolic Space NeurIPS 2023 Negative curvature obstructs acceleration for strongly geodesically convex optimization, even with exact first-order oracles COLT 2022 Noisy Riemannian Gradient Descent for Eigenvalue Computation with Application to Inexact Stochastic Recursive Gradient Algorithm ACML 2022 Provable Tensor-Train Format Tensor Completion by Riemannian Optimization JMLR 2022 Distributed Principal Component Analysis with Limited Communication NeurIPS 2021 Tight Convergence Rate of Gradient Descent for Eigenvalue Computation IJCAI 2020 A Nonconvex Approach for Exact and Efficient Multichannel Sparse Blind Deconvolution NeurIPS 2019 Efficiently escaping saddle points on manifolds NeurIPS 2019 Minimum Stein Discrepancy Estimators NeurIPS 2019 Trivializations for Gradient-Based Optimization on Manifolds NeurIPS 2019