1 citations · 1 across the 2 of their papers we have counts for
12 papers
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…
Cardinal Optimizer (COPT) User Guide
Dongdong Ge, Qi Huangfu, Zizhuo Wang +2
Cardinal Optimizer is a high-performance mathematical programming solver for efficiently solving largescale optimization problem. This documentation provides basic introduction to…
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…
Data-driven Mixed Integer Optimization through Probabilistic Multi-variable Branching
Yanguang Chen, Wenzhi Gao, Wanyu Zhang +3
In this paper, we propose a Pre-trained Mixed Integer Optimization framework (PreMIO) that accelerates online mixed integer program (MIP) solving with offline datasets and machine…
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…