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Riemannian optimization

Optimization methods on Riemannian manifolds.

Papers

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Showing 1–25 of 153 papers

TitleStatusHype
Riemannian Optimization on Relaxed Indicator Matrix ManifoldCode2
FireANTs: Adaptive Riemannian Optimization for Multi-Scale Diffeomorphic MatchingCode2
Symmetric Spaces for Graph Embeddings: A Finsler-Riemannian ApproachCode2
Geoopt: Riemannian Optimization in PyTorchCode2
Geomstats: A Python Package for Riemannian Geometry in Machine LearningCode2
Riemannian Adaptive Optimization MethodsCode2
geomstats: a Python Package for Riemannian Geometry in Machine LearningCode2
Fast hyperboloid decision tree algorithmsCode1
Graph Neural Networks on SPD Manifolds for Motor Imagery Classification: A Perspective from the Time-Frequency AnalysisCode1
Projective Manifold Gradient Layer for Deep Rotation RegressionCode1
Tensor-Train Density EstimationCode1
Poincaré Embeddings for Learning Hierarchical RepresentationsCode1
Leveraging Low-rank Factorizations of Conditional Correlation Matrices in Graph Learning—0
PoLAR: Polar-Decomposed Low-Rank Adapter Representation—0
Efficient Optimization with Orthogonality Constraint: a Randomized Riemannian Submanifold MethodCode0
Riemannian Optimization on the Oblique Manifold for Sparse Simplex Constraints via Multiplicative Updates—0
Differential Evolution for Grassmann Manifold Optimization: A Projection Approach—0
Higher Order Reduced Rank Regression—0
Multi-view Spectral Clustering on the Grassmannian Manifold With Hypergraph Representation—0
The Distributionally Robust Optimization Model of Sparse Principal Component Analysis—0
Fast, Accurate Manifold Denoising by Tunneling Riemannian Optimization—0
Spectral-factorized Positive-definite Curvature Learning for NN Training—0
Causal Abstraction Learning based on the Semantic Embedding PrincipleCode0
A Riemannian Optimization Perspective of the Gauss-Newton Method for Feedforward Neural Networks—0
A Spectral Framework for Tracking Communities in Evolving NetworksCode0
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