Large-scale riemannian meta-optimization via subspace adaptation

P Yu, Y Wu, Z Gao, X Fan, Y Jia - Computer Vision and Image …, 2025 - Elsevier
Riemannian meta-optimization provides a promising approach to solving non-linear
constrained optimization problems, which trains neural networks as optimizers to perform …

Rcoco: contrastive collective link prediction across multiplex network in riemannian space

L Sun, M Li, Y Yang, X Li, L Liu, P Zhang… - International Journal of …, 2024 - Springer
Link prediction typically studies the probability of future interconnection among nodes with
the observation in a single social network. More often than not, real scenario is presented as …

Efficient Riemannian meta-optimization by implicit differentiation

X Fan, Y Wu, Z Gao, Y Jia, M Harandi - Proceedings of the AAAI …, 2022 - ojs.aaai.org
To solve optimization problems with nonlinear constrains, the recently developed
Riemannian meta-optimization methods show promise, which train neural networks as an …

Riemannian accelerated zeroth-order algorithm: improved robustness and lower query complexity

C He, Z Pan, X Wang, B Jiang - arxiv preprint arxiv:2405.05713, 2024 - arxiv.org
Optimization problems with access to only zeroth-order information of the objective function
on Riemannian manifolds arise in various applications, spanning from statistical learning to …