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riemannian optimization

89 papers

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Co-occurring keywords

manifold optimization (67) stiefel manifold (29) gradient descent (1143) matrix completion (356) riemannian manifold (169) geodesic convexity (19) non-convex optimization (546) matrix factorization (529) stochastic gradient (296) optimal transport (945)

Papers

RoZO: Geometry-Aware Zeroth-Order Fine-Tuning on Low-Rank Adapters for Black-Box Large Language Models EACL 2026
Parallelizable Riemannian Alternating Direction Method of Multipliers for Non-convex Pose Graph Optimization AAAI 2026
Test-time Diverse Reasoning by Riemannian Activation Steering AAAI 2026
Decentralized Projected Riemannian Stochastic Recursive Momentum Method for Nonconvex Optimization AAAI 2025
Riemannian Optimization for LoRA on the Stiefel Manifold EMNLP 2025
Riemannian Direct Trajectory Optimization of Rigid Bodies on Matrix Lie Groups RSS 2025
Guaranteed Nonconvex Factorization Approach for Tensor Train Recovery JMLR 2024
Block-Diagonal Orthogonal Relation and Matrix Entity for Knowledge Graph Embedding EMNLP 2024
Faster Randomized Methods for Orthogonality Constrained Problems JMLR 2024
Training a Tucker Model With Shared Factors: a Riemannian Optimization Approach AISTATS 2024
Guiding Neural Collapse: Optimising Towards the Nearest Simplex Equiangular Tight Frame NIPS 2024
Infeasible Deterministic, Stochastic, and Variance-Reduction Algorithms for Optimization under Orthogonality Constraints JMLR 2024
Riemannian Accelerated Gradient Methods via Extrapolation AISTATS 2023
Global optimality for Euclidean CCCP under Riemannian convexity ICML 2023
Riemannian SAM: Sharpness-Aware Minimization on Riemannian Manifolds NIPS 2023
Get the Best of Both Worlds: Improving Accuracy and Transferability by Grassmann Class Representation ICCV 2023
Riemannian stochastic optimization methods avoid strict saddle points NIPS 2023
Adaptive Riemannian stochastic gradient descent and reparameterization for Gaussian mixture model fitting ACML 2023
Simplifying Momentum-based Positive-definite Submanifold Optimization with Applications to Deep Learning ICML 2023
Incremental Aggregated Riemannian Gradient Method for Distributed PCA AISTATS 2023
Low-rank Tensor Estimation via Riemannian Gauss-Newton: Statistical Optimality and Second-Order Convergence JMLR 2023
A Riemannian Exponential Augmented Lagrangian Method for Computing the Projection Robust Wasserstein Distance NIPS 2023
Accelerated Riemannian Optimization: Handling Constraints with a Prox to Bound Geometric Penalties COLT 2023
Decentralized Riemannian Algorithm for Nonconvex Minimax Problems AAAI 2023
Accelerated Gradient Methods for Geodesically Convex Optimization: Tractable Algorithms and Convergence Analysis ICML 2022