geodesic convexity

Accelerated Methods for Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties AISTATS 2025 Accelerated Riemannian Optimization: Handling Constraints with a Prox to Bound Geometric Penalties COLT 2023 Curvature and complexity: Better lower bounds for geodesically convex optimization COLT 2023 Geodesically convex M-estimation in metric spaces COLT 2023 Global optimality for Euclidean CCCP under Riemannian convexity ICML 2023 Open Problem: Polynomial linearly-convergent method for g-convex optimization? COLT 2023 Riemannian Projection-free Online Learning NeurIPS 2023 Accelerated Gradient Methods for Geodesically Convex Optimization: Tractable Algorithms and Convergence Analysis ICML 2022 First-Order Algorithms for Min-Max Optimization in Geodesic Metric Spaces NeurIPS 2022 Global Riemannian Acceleration in Hyperbolic and Spherical Spaces ALT 2022 Negative curvature obstructs acceleration for strongly geodesically convex optimization, even with exact first-order oracles COLT 2022 Active Learning of Convex Halfspaces on Graphs NeurIPS 2021 A No-go Theorem for Robust Acceleration in the Hyperbolic Plane NeurIPS 2021 Averaging on the Bures-Wasserstein manifold: dimension-free convergence of gradient descent NeurIPS 2021 Momentum Improves Optimization on Riemannian Manifolds AISTATS 2021 On Riemannian Optimization over Positive Definite Matrices with the Bures-Wasserstein Geometry NeurIPS 2021 Geodesically-convex optimization for averaging partially observed covariance matrices ACML 2020 The Wasserstein Proximal Gradient Algorithm NeurIPS 2020 Sampling and Optimization on Convex Sets in Riemannian Manifolds of Non-Negative Curvature COLT 2019 Averaging Stochastic Gradient Descent on Riemannian Manifolds COLT 2018 Geometric optimisation on positive definite matrices for elliptically contoured distributions NeurIPS 2013