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Riemannian optimization

Optimization methods on Riemannian manifolds.

Papers

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Showing 51–100 of 153 papers

TitleStatusHype
Wasserstein Gradient Flows for Optimizing Gaussian Mixture Policies—0
Structured Low-Rank Tensor Learning—0
Low-complexity subspace-descent over symmetric positive definite manifoldCode0
Infeasible Deterministic, Stochastic, and Variance-Reduction Algorithms for Optimization under Orthogonality ConstraintsCode0
Faster Riemannian Newton-type Optimization by Subsampling and Cubic Regularization—0
Riemannian Stochastic Approximation for Minimizing Tame Nonsmooth Objective Functions—0
Riemannian Optimization for Variance Estimation in Linear Mixed Models—0
Accelerated Riemannian Optimization: Handling Constraints with a Prox to Bound Geometric Penalties—0
A Riemannian ADMMCode0
Learning Graphical Factor Models with Riemannian OptimizationCode0
Rieoptax: Riemannian Optimization in JAXCode0
Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian ManifoldCode0
Riemannian optimization for non-centered mixture of scaled Gaussian distributionsCode0
Manifold Free Riemannian Optimization—0
A Variance-Reduced Stochastic Gradient Tracking Algorithm for Decentralized Optimization with Orthogonality Constraints—0
On a class of geodesically convex optimization problems solved via Euclidean MM methods—0
Tensor-on-Tensor Regression: Riemannian Optimization, Over-parameterization, Statistical-computational Gap, and Their InterplayCode0
Riemannian CUR Decompositions for Robust Principal Component Analysis—0
Riemannian stochastic approximation algorithms—0
Differentially private Riemannian optimization—0
Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNsCode0
Riemannian Hamiltonian methods for min-max optimization on manifolds—0
Riemannian block SPD coupling manifold and its application to optimal transportCode0
Manifold Optimization Methods for Hybrid beamforming in mmWave Dual-Function Radar-Communication System—0
Understanding Riemannian Acceleration via a Proximal Extragradient Framework—0
On Geometric Connections of Embedded and Quotient Geometries in Riemannian Fixed-rank Matrix Optimization—0
Learning with symmetric positive definite matrices via generalized Bures-Wasserstein geometryCode0
Tensor train completion: local recovery guarantees via Riemannian optimization—0
On Riemannian Approach for Constrained Optimization Model in Extreme Classification Problems—0
Nonlinear matrix recovery using optimization on the Grassmann manifoldCode0
Provable Tensor-Train Format Tensor Completion by Riemannian Optimization—0
Vector Transport Free Riemannian LBFGS for Optimization on Symmetric Positive Definite Matrix ManifoldsCode0
Faster Randomized Methods for Orthogonality Constrained Problems—0
On Riemannian Optimization over Positive Definite Matrices with the Bures-Wasserstein GeometryCode0
Accurate and fast matrix factorization for low-rank learningCode0
Automatic differentiation for Riemannian optimization on low-rank matrix and tensor-train manifolds—0
Projection Robust Wasserstein Barycenters—0
Approximate Birkhoff-von-Neumann decomposition: a differentiable approach—0
Fast Global Convergence for Low-rank Matrix Recovery via Riemannian Gradient Descent with Random Initialization—0
Escape saddle points faster on manifolds via perturbed Riemannian stochastic recursive gradient—0
Operator-valued formulas for Riemannian Gradient and Hessian and families of tractable metricsCode0
Robust Low-rank Matrix Completion via an Alternating Manifold Proximal Gradient Continuation Method—0
Riemannian stochastic recursive momentum method for non-convex optimization—0
Representation Learning via Adversarially-Contrastive Optimal Transport—0
Variance reduction for Riemannian non-convex optimization with batch size adaptation—0
Projection Robust Wasserstein Distance and Riemannian Optimization—0
Riemannian geometry for Compound Gaussian distributions: application to recursive change detection—0
Riemannian Stochastic Proximal Gradient Methods for Nonsmooth Optimization over the Stiefel Manifold—0
Stochastic Zeroth-order Riemannian Derivative Estimation and Optimization—0
Affinity guided Geometric Semi-Supervised Metric Learning—0
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