1 citations · 1 across the 3 of their papers we have counts for
5 papers
Accelerating Trust-Region Methods: An Attempt to Balance Global and Local Efficiency
Yuntian Jiang, Chuwen Zhang, Bo Jiang +1
Balancing global efficiency and local convergence remains a central challenge in second-order methods for unconstrained convex optimization problems. Newton's method enjoys fast lo…
Homogeneous second-order descent framework: a fast alternative to Newton-type methods
Chang He, Yuntian Jiang, Chuwen Zhang +3
This paper proposes a homogeneous second-order descent framework (HSODF) for nonconvex and convex optimization based on the generalized homogeneous model (GHM). In comparison to th…
A homogeneous second-order descent method for nonconvex optimization
Chuwen Zhang, Dongdong Ge, Chang He +4
In this paper, we introduce a Homogeneous Second-Order Descent Method (HSODM) using the homogenized quadratic approximation to the original function. The merit of homogenization is…
Beyond Nonconvexity: A Universal Trust-Region Method with New Analyses
Yuntian Jiang, Chang He, Chuwen Zhang +3
The trust-region (TR) method is renowned historically for its robustness in nonconvex problems and extraordinary numerical performance, but the study of its performance in convex o…
History-Aware Adaptive High-Order Tensor Regularization
Chang He, Bo Jiang, Yuntian Jiang +2
In this paper, we develop a new adaptive regularization method for minimizing a composite function, which is the sum of a th-order () Lipschitz continuous function and…