2 papers
math.OC2026
Recursive Gradient Retraction Methods for Stochastic Nonconvex Optimization on Stiefel Manifolds
Zhijie Yuan, Lei Sun, Ganzhao Yuan
Nonconvex optimization on Stiefel manifolds underlies many problems in machine learning and deep learning. However, existing stochastic Riemannian retraction methods often rely on…
math.OC2024
Block Coordinate Descent Methods for Structured Nonconvex Optimization with Nonseparable Constraints: Optimality Conditions and Global Convergence
Zhijie Yuan, Ganzhao Yuan, Lei Sun
Coordinate descent algorithms are widely used in machine learning and large-scale data analysis due to their strong optimality guarantees and impressive empirical performance in so…