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Riemannian optimization

Optimization methods on Riemannian manifolds.

Papers

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Showing 101–150 of 153 papers

TitleStatusHype
Learning Weighted Submanifolds with Variational Autoencoders and Riemannian Variational Autoencoders—0
Coupling Matrix Manifolds and Their Applications in Optimal Transport—0
Spherical Text EmbeddingCode0
Hyperbolic Node Embedding for Signed Networks—0
GODS: Generalized One-class Discriminative Subspaces for Anomaly Detection—0
Riemannian optimization on the simplex of positive definite matrices—0
Optimal low rank tensor recovery—0
Learning Mixed-Curvature Representations in Product Spaces—0
Block-Coordinate Minimization for Large SDPs with Block-Diagonal Constraints—0
Riemannian joint dimensionality reduction and dictionary learning on symmetric positive definite manifold—0
Riemannian optimization with a preconditioning scheme on the generalized Stiefel manifold—0
Hamiltonian Monte-Carlo for Orthogonal Matrices—0
Accelerated Inference in Markov Random Fields via Smooth Riemannian OptimizationCode0
Riemannian Adaptive Optimization MethodsCode2
Learning Discriminative Video Representations Using Adversarial Perturbations—0
Contrastive Video Representation Learning via Adversarial Perturbations—0
Low-Rank Riemannian Optimization on Positive Semidefinite Stochastic Matrices with Applications to Graph Clustering—0
Geometry Aware Constrained Optimization Techniques for Deep Learning—0
geomstats: a Python Package for Riemannian Geometry in Machine LearningCode2
Non-Linear Temporal Subspace Representations for Activity Recognition—0
Provably robust estimation of modulo 1 samples of a smooth function with applications to phase unwrapping—0
Averaging Stochastic Gradient Descent on Riemannian Manifolds—0
A dual framework for low-rank tensor completion—0
Dimensionality Reduction on Grassmannian via Riemannian Optimization: A Generalized Perspective—0
Riemannian Optimization via Frank-Wolfe MethodsCode0
Learning Discriminative ab-Divergences for Positive Definite Matrices—0
Tensor Networks for Dimensionality Reduction and Large-Scale Optimizations. Part 2 Applications and Future PerspectivesCode0
Learning Discriminative Alpha-Beta-divergence for Positive Definite Matrices (Extended Version)—0
An Alternative to EM for Gaussian Mixture Models: Batch and Stochastic Riemannian OptimizationCode0
Sequence Summarization Using Order-constrained Kernelized Feature Subspaces—0
Poincaré Embeddings for Learning Hierarchical RepresentationsCode1
Riemannian Optimization for Skip-Gram Negative SamplingCode0
Generalized Rank Pooling for Activity Recognition—0
A Manifold Approach to Learning Mutually Orthogonal Subspaces—0
Riemannian stochastic variance reduced gradient algorithm with retraction and vector transportCode0
Learning an Invariant Hilbert Space for Domain Adaptation—0
Riemannian Tensor Completion with Side Information—0
Geometric Mean Metric LearningCode0
Low-rank tensor completion: a Riemannian manifold preconditioning approach—0
Riemannian stochastic variance reduced gradient on Grassmann manifoldCode0
Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds—0
Exponential MachinesCode0
Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic DifferentiationCode0
Matrix Manifold Optimization for Gaussian Mixtures—0
MixEst: An Estimation Toolbox for Mixture ModelsCode0
Riemannian Dictionary Learning and Sparse Coding for Positive Definite Matrices—0
Manifold Optimization for Gaussian Mixture Models—0
Riemannian preconditioning for tensor completion—0
Convergence results for projected line-search methods on varieties of low-rank matrices via Łojasiewicz inequality—0
Geometric optimisation on positive definite matrices for elliptically contoured distributions—0
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