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Riemannian optimization

Optimization methods on Riemannian manifolds.

Papers

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Showing 51–100 of 153 papers

TitleStatusHype
Matrix Manifold Optimization for Gaussian Mixtures—0
Multichannel Active Noise Control with Exterior Radiation Suppression Based on Riemannian Optimization—0
Multi-view Spectral Clustering on the Grassmannian Manifold With Hypergraph Representation—0
Near-Optimal differentially private low-rank trace regression with guaranteed private initialization—0
Non-Linear Temporal Subspace Representations for Activity Recognition—0
On a class of geodesically convex optimization problems solved via Euclidean MM methods—0
On Geometric Connections of Embedded and Quotient Geometries in Riemannian Fixed-rank Matrix Optimization—0
On Riemannian Approach for Constrained Optimization Model in Extreme Classification Problems—0
Optimal low rank tensor recovery—0
PoLAR: Polar-Decomposed Low-Rank Adapter Representation—0
Projection Robust Wasserstein Barycenters—0
Projection Robust Wasserstein Distance and Riemannian Optimization—0
Provable Tensor-Train Format Tensor Completion by Riemannian Optimization—0
Provably robust estimation of modulo 1 samples of a smooth function with applications to phase unwrapping—0
R3MC: A Riemannian three-factor algorithm for low-rank matrix completion—0
Riemannian optimization with a preconditioning scheme on the generalized Stiefel manifold—0
Representation Learning via Adversarially-Contrastive Optimal Transport—0
Riemannian coordinate descent algorithms on matrix manifolds—0
Riemannian CUR Decompositions for Robust Principal Component Analysis—0
Riemannian Dictionary Learning and Sparse Coding for Positive Definite Matrices—0
Riemannian geometry for Compound Gaussian distributions: application to recursive change detection—0
Riemannian Hamiltonian methods for min-max optimization on manifolds—0
Riemannian joint dimensionality reduction and dictionary learning on symmetric positive definite manifold—0
Riemannian Low-Rank Model Compression for Federated Learning with Over-the-Air Aggregation—0
Riemannian Optimization on the Oblique Manifold for Sparse Simplex Constraints via Multiplicative Updates—0
Riemannian Optimization for Non-convex Euclidean Distance Geometry with Global Recovery Guarantees—0
Riemannian Optimization for Variance Estimation in Linear Mixed Models—0
Riemannian optimization on the simplex of positive definite matrices—0
Riemannian preconditioning for tensor completion—0
Riemannian Self-Attention Mechanism for SPD Networks—0
Riemannian Stochastic Approximation for Minimizing Tame Nonsmooth Objective Functions—0
Riemannian stochastic optimization methods avoid strict saddle points—0
Riemannian Stochastic Proximal Gradient Methods for Nonsmooth Optimization over the Stiefel Manifold—0
Riemannian stochastic recursive momentum method for non-convex optimization—0
Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds—0
Riemannian Tensor Completion with Side Information—0
Robust Low-rank Matrix Completion via an Alternating Manifold Proximal Gradient Continuation Method—0
Sequence Summarization Using Order-constrained Kernelized Feature Subspaces—0
Spectral-factorized Positive-definite Curvature Learning for NN Training—0
Stochastic gradient descent on Riemannian manifolds—0
Streamlining in the Riemannian Realm: Efficient Riemannian Optimization with Loopless Variance Reduction—0
Structured Low-Rank Tensor Learning—0
Structured Regularization for Constrained Optimization on the SPD Manifold—0
Symplectic Structure-Aware Hamiltonian (Graph) Embeddings—0
Tensor train completion: local recovery guarantees via Riemannian optimization—0
The Distributionally Robust Optimization Model of Sparse Principal Component Analysis—0
Riemannian stochastic approximation algorithms—0
The Fisher-Rao geometry of CES distributions—0
Variance Reduction and Quasi-Newton for Particle-Based Variational Inference—0
Variance reduction for Riemannian non-convex optimization with batch size adaptation—0
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