SOTAVerified

Riemannian optimization

Optimization methods on Riemannian manifolds.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–100 of 153 papers

TitleStatusHype
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
Wasserstein Gradient Flows for Optimizing Gaussian Mixture Policies—0
Worst-Case Riemannian Optimization with Uncertain Target Steering Vector for Slow-Time Transmit Sequence of Cognitive Radar—0
Leveraging Low-rank Factorizations of Conditional Correlation Matrices in Graph Learning—0
Gaussian-Mixture-Model Q-Functions for Reinforcement Learning by Riemannian Optimization—0
A Riemannian Optimization Perspective of the Gauss-Newton Method for Feedforward Neural Networks—0
Generalized Rank Pooling for Activity Recognition—0
Geometric optimisation on positive definite matrices for elliptically contoured distributions—0
Geometry Aware Constrained Optimization Techniques for Deep Learning—0
GODS: Generalized One-class Discriminative Subspaces for Anomaly Detection—0
Hamiltonian Monte-Carlo for Orthogonal Matrices—0
Higher Order Reduced Rank Regression—0
Hyperbolic Node Embedding for Signed Networks—0
Hyperboloid GPLVM for Discovering Continuous Hierarchies via Nonparametric Estimation—0
Learning an Invariant Hilbert Space for Domain Adaptation—0
Learning Discriminative ab-Divergences for Positive Definite Matrices—0
Learning Discriminative Alpha-Beta-divergence for Positive Definite Matrices (Extended Version)—0
Contrastive Video Representation Learning via Adversarial Perturbations—0
Learning Discriminative Video Representations Using Adversarial Perturbations—0
Learning Mixed-Curvature Representations in Product Spaces—0
Learning Weighted Submanifolds with Variational Autoencoders and Riemannian Variational Autoencoders—0
Low-Rank Riemannian Optimization on Positive Semidefinite Stochastic Matrices with Applications to Graph Clustering—0
Low-rank tensor completion: a Riemannian manifold preconditioning approach—0
Manifold Free Riemannian Optimization—0
Manifold Optimization for Gaussian Mixture Models—0
Manifold Optimization Methods for Hybrid beamforming in mmWave Dual-Function Radar-Communication System—0
Manopt, a Matlab toolbox for optimization on manifolds—0
Show:102550
← PrevPage 2 of 4Next →

No leaderboard results yet.