10 papers
An Inexact Halpern-accelerated Preconditioned Generalized Proximal Point Algorithm for the Maximal Monotone Inclusion Problem
Lei Yang, Haihang Lan, Di Hou +2
This paper studies an inexact Halpern-accelerated generalized proximal point algorithm with an admissible positive semidefinite preconditioner for solving maximal mon…
Newton Method for Fixed-Support Doubly Entropic Wasserstein Barycenter
Jianting Pan, Sirong Dai, Lei Yang +3
We study the fixed-support doubly regularized Wasserstein barycenter problem. Using the semi-dual formulation of entropic optimal transport, we reformulate the problem as a smooth,…
Mixed-Precision GPU Acceleration for Large-Scale Minimum Enclosing Ball Problems
Ling Liang, Lei Yang
A mixed-precision GPU-oriented optimization framework is developed for computing the minimum enclosing ball of a collection of balls. The approach is built on an equivalent second-…
A Provably Convergent and Practical Algorithm for Gromov--Wasserstein Optimal Transport
Ling Liang, Lei Yang
Gromov--Wasserstein optimal transport (GWOT) aligns metric measure spaces by matching their within-domain relational structures, but large-scale GWOT remains challenging because it…
D-ripALM: A Tuning-friendly Decentralized Relative-Type Inexact Proximal Augmented Lagrangian Method
Jiayi Zhu, Hong Wang, Ling Liang +1
This paper proposes D-ripALM, a Decentralized relative-type inexact proximal Augmented Lagrangian Method for consensus convex optimization over multi-agent networks. D-ripALM adopt…
Convergence Analysis of a Relative-type Inexact Preconditioned Proximal ALM for Convex Nonlinear Programming
Lei Yang, Jiayi Zhu, Ling Liang +1
This article investigates the convergence properties of a relative-type inexact preconditioned proximal augmented Lagrangian method (ripALM) for convex nonlinear programming, a…
ripALM: A Relative-Type Inexact Proximal Augmented Lagrangian Method for Linearly Constrained Convex Optimization
Jiayi Zhu, Ling Liang, Lei Yang +1
Inexact proximal augmented Lagrangian methods (ipALMs) have been widely used for solving linearly constrained convex optimization problems, owing to their strong theoretical guaran…
An Inexact Bregman Proximal Difference-of-Convex Algorithm with Two Types of Relative Stopping Criteria
Lei Yang, Jingjing Hu, Kim-Chuan Toh
In this paper, we consider a class of difference-of-convex (DC) optimization problems, which require only a weaker restricted -smooth adaptable property on the smooth part of th…
A Corrected Inexact Proximal Augmented Lagrangian Method with a Relative Error Criterion for a Class of Group-quadratic Regularized Optimal Transport Problems
Lei Yang, Ling Liang, Hong T. M. Chu +1
The optimal transport (OT) problem and its related problems have attracted significant attention and have been extensively studied in various applications. In this paper, we focus…
Inexact Bregman Proximal Gradient Method and its Inertial Variant with Absolute and Partial Relative Stopping Criteria
Lei Yang, Kim-Chuan Toh
The Bregman proximal gradient method (BPGM), which uses the Bregman distance as a proximity measure in the iterative scheme, has recently been re-developed for minimizing convex co…