most citedHomogeneous second-order descent framework: a fast alternative to Newton-type methods

1 citations · 1 across the 5 of their papers we have counts for

collaborators

11 papers

math.OC2026

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…

math.OC20261 cited

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…

math.OC2026

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…

cs.GT2026

Rationalizing collective revealed preferences with an application in fair resource allocation

Chuwen Zhang, Zhiyun Guo, Zizhuo Wang +1

This paper presents a revealed preference approach for rationalizing collective consumption behavior. We introduce the Constructive Rationalization Method (CRM), which approximates…

cs.CY2026

The Dynamic and Endogenous Behavior of Re-Offense Risk: An Agent-Based Simulation Study of Treatment Allocation in Incarceration Diversion Programs

Chuwen Zhang, Pengyi Shi, Amy Ward

Incarceration-diversion treatment programs aim to improve societal reintegration and reduce recidivism, but limited capacity forces policymakers to make prioritization decisions th…

math.OC2026

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…