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Riemannian optimization

Optimization methods on Riemannian manifolds.

Papers

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Showing 101–150 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
Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNsCode0
The Gaussian Discriminant Variational Autoencoder (GdVAE): A Self-Explainable Model with Counterfactual ExplanationsCode0
Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian ManifoldCode0
Learning with symmetric positive definite matrices via generalized Bures-Wasserstein geometryCode0
Nonlinear matrix recovery using optimization on the Grassmann manifoldCode0
Geometric Mean Metric LearningCode0
Rieoptax: Riemannian Optimization in JAXCode0
Accelerated Inference in Markov Random Fields via Smooth Riemannian OptimizationCode0
Exponential MachinesCode0
Elliptical Wishart distributions: information geometry, maximum likelihood estimator, performance analysis and statistical learningCode0
Efficient Optimization with Orthogonality Constraint: a Randomized Riemannian Submanifold MethodCode0
Riemannian Optimization via Frank-Wolfe MethodsCode0
Causal Abstraction Learning based on the Semantic Embedding PrincipleCode0
Accurate and fast matrix factorization for low-rank learningCode0
On Riemannian Optimization over Positive Definite Matrices with the Bures-Wasserstein GeometryCode0
Operator-valued formulas for Riemannian Gradient and Hessian and families of tractable metricsCode0
Vector Transport Free Riemannian LBFGS for Optimization on Symmetric Positive Definite Matrix ManifoldsCode0
Infeasible Deterministic, Stochastic, and Variance-Reduction Algorithms for Optimization under Orthogonality ConstraintsCode0
Optimal Matrix-Mimetic Tensor Algebras via Variable ProjectionCode0
Optimization without Retraction on the Random Generalized Stiefel ManifoldCode0
Block-Diagonal Orthogonal Relation and Matrix Entity for Knowledge Graph EmbeddingCode0
Spherical Text EmbeddingCode0
Tensor Networks for Dimensionality Reduction and Large-Scale Optimizations. Part 2 Applications and Future PerspectivesCode0
Learning Graphical Factor Models with Riemannian OptimizationCode0
Riemannian stochastic variance reduced gradient on Grassmann manifoldCode0
A Spectral Framework for Tracking Communities in Evolving NetworksCode0
Low-complexity subspace-descent over symmetric positive definite manifoldCode0
Riemannian optimization for non-centered mixture of scaled Gaussian distributionsCode0
Riemannian stochastic variance reduced gradient algorithm with retraction and vector transportCode0
Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic DifferentiationCode0
Riemannian Optimization for Skip-Gram Negative SamplingCode0
Tensor-on-Tensor Regression: Riemannian Optimization, Over-parameterization, Statistical-computational Gap, and Their InterplayCode0
Registration of algebraic varieties using Riemannian optimizationCode0
An Alternative to EM for Gaussian Mixture Models: Batch and Stochastic Riemannian OptimizationCode0
Meta-Learning with Generalized Ridge Regression: High-dimensional Asymptotics, Optimality and Hyper-covariance EstimationCode0
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