riemannian optimization

Incremental Aggregated Riemannian Gradient Method for Distributed PCA AISTATS 2023 Low-rank Tensor Estimation via Riemannian Gauss-Newton: Statistical Optimality and Second-Order Convergence JMLR 2023 Riemannian Accelerated Gradient Methods via Extrapolation AISTATS 2023 Riemannian SAM: Sharpness-Aware Minimization on Riemannian Manifolds NeurIPS 2023 Riemannian stochastic optimization methods avoid strict saddle points NeurIPS 2023 Simplifying Momentum-based Positive-definite Submanifold Optimization with Applications to Deep Learning ICML 2023 Accelerated Gradient Methods for Geodesically Convex Optimization: Tractable Algorithms and Convergence Analysis ICML 2022 Accelerated Multiplicative Weights Update Avoids Saddle Points Almost Always IJCAI 2022 ARCS: Accurate Rotation and Correspondence Search CVPR 2022 Coordinate Descent on the Orthogonal Group for Recurrent Neural Network Training AAAI 2022 Efficient Riemannian Meta-Optimization by Implicit Differentiation AAAI 2022 Fast and Efficient MMD-Based Fair PCA via Optimization over Stiefel Manifold AAAI 2022 Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNs AAAI 2022 Global Riemannian Acceleration in Hyperbolic and Spherical Spaces ALT 2022 Projective Manifold Gradient Layer for Deep Rotation Regression CVPR 2022 Provable Tensor-Train Format Tensor Completion by Riemannian Optimization JMLR 2022 Riemannian Stochastic Proximal Gradient Methods for Nonsmooth Optimization over the Stiefel Manifold JMLR 2022 The Dynamics of Riemannian Robbins-Monro Algorithms COLT 2022 Understanding Riemannian Acceleration via a Proximal Extragradient Framework COLT 2022 A No-go Theorem for Robust Acceleration in the Hyperbolic Plane NeurIPS 2021 An Online Riemannian PCA for Stochastic Canonical Correlation Analysis NeurIPS 2021 A Riemannian Block Coordinate Descent Method for Computing the Projection Robust Wasserstein Distance ICML 2021 Averaging on the Bures-Wasserstein manifold: dimension-free convergence of gradient descent NeurIPS 2021 Decentralized Riemannian Gradient Descent on the Stiefel Manifold ICML 2021 Dual Principal Component Pursuit for Learning a Union of Hyperplanes: Theory and Algorithms AISTATS 2021