3 citations · 7 across the 14 of their papers we have counts for
14 papers
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…
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…
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…
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…
The Second-Order Tâtonnement: Decentralized Interior-Point Methods for Market Equilibrium
Chuwen Zhang, Chang He, Bo Jiang +1
The tâtonnement process and Smale's process are two classical approaches to compute market equilibrium in exchange economies. While the tâtonnement process can be seen as a first-o…
A Customized Augmented Lagrangian Method for Block-Structured Integer Programming
Rui Wang, Chuwen Zhang, Shanwen Pu +2
Integer programming with block structures has received considerable attention recently and is widely used in many practical applications such as train timetabling and vehicle routi…
cuPDLP-C: A Strengthened Implementation of cuPDLP for Linear Programming by C language
Haihao Lu, Jinwen Yang, Haodong Hu +6
A recent GPU implementation of the Restarted Primal-Dual Hybrid Gradient Method for Linear Programming was proposed in Lu and Yang (2023). Its computational results demonstrate the…
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…
Trust Region Methods For Nonconvex Stochastic Optimization Beyond Lipschitz Smoothness
Chenghan Xie, Chenxi Li, Chuwen Zhang +3
In many important machine learning applications, the standard assumption of having a globally Lipschitz continuous gradient may fail to hold. This paper delves into a more general…
A Homogenization Approach for Gradient-Dominated Stochastic Optimization
Jiyuan Tan, Chenyu Xue, Chuwen Zhang +3
Gradient dominance property is a condition weaker than strong convexity, yet sufficiently ensures global convergence even in non-convex optimization. This property finds wide appli…
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…
An Enhanced ADMM-based Interior Point Method for Linear and Conic Optimization
Qi Deng, Qing Feng, Wenzhi Gao +8
The ADMM-based interior point (ABIP, Lin et al. 2021) method is a hybrid algorithm that effectively combines interior point method (IPM) and first-order methods to achieve a perfor…
DRSOM: A Dimension Reduced Second-Order Method
Chuwen Zhang, Dongdong Ge, Chang He +3
In this paper, we propose a Dimension-Reduced Second-Order Method (DRSOM) for convex and nonconvex (unconstrained) optimization. Under a trust-region-like framework, our method pre…