13 papers
MoSSP: A Momentum-Based Single-Loop Stochastic Penalty Method for Nonconvex Constrained DC-Regularized Optimization
Luxuan Li, Chunfeng Cui, Xiao Wang
In this paper, we study a structured class of nonconvex constrained stochastic problems with difference-of-convex (DC) regularization, where the feasible set is possibly nonconvex…
Blind Hyperspectral and Multispectral Images Fusion: A Unified Tensor Fusion Framework from Coupled Inverse Problem Perspective
Ying Gao, Michael K. Ng, Chunfeng cui
Hyperspectral and multispectral images fusion aims at integrating a low-resolution hyperspectral image (LR-HSI) and a high-resolution multispectral image (HR-MSI) to construct a hi…
Narrowing the Gap: SOS Ranks of Biquadratic Forms and a Lower Bound of
Yi Xu, Chunfeng Cui, Liqun Qi
We investigate the maximum sum-of-squares (SOS) rank of biquadratic forms in the critical case of variables, where the general bounds are currently $7 \leq \mathrm{BSR…
Parallelizable Riemannian Alternating Direction Method of Multipliers for Non-convex Pose Graph Optimization
Xin Chen, Chunfeng Cui, Deren Han +1
Pose graph optimization (PGO) is fundamental to robot perception and navigation systems, serving as the mathematical backbone for solving simultaneous localization and mapping (SLA…
Projecting onto the unit dual quaternion set
Ziyang Li, Chunfeng Cui, Jiaxin Xie
Dual quaternions have gained significant attention due to their wide applications in areas such as multi-agent formation control, 3D motion modeling, and robotics. A fundamental as…
DualHash: A Stochastic Primal-Dual Algorithm with Theoretical Guarantee for Deep Hashing
Luxuan Li, Xiao Wang, Chunfeng Cui
Deep hashing converts high-dimensional feature vectors into compact binary codes, enabling efficient large-scale retrieval. A fundamental challenge in deep hashing stems from the d…
An Accelerated Alternating Partial Bregman Algorithm for ReLU-based Matrix Decomposition
Qingsong Wang, Yunfei Qu, Chunfeng Cui +1
Despite the remarkable success of low-rank estimation in data mining, its effectiveness diminishes when applied to data that inherently lacks low-rank structure. To address this li…
Multi-step Inertial Accelerated Doubly Stochastic Gradient Methods for Block Term Tensor Decomposition
Zehui Liu, Qingsong Wang, Chunfeng Cui
In this paper, we explore a specific optimization problem that combines a differentiable nonconvex function with a nondifferentiable function for multi-block variables, which is pa…
Extended alternating structure-adapted proximal gradient algorithm for nonconvex nonsmooth problems
Ying Gao, Chunfeng Cui, Wenxing Zhang +1
Alternating structure-adapted proximal (ASAP) gradient algorithm (M. Nikolova and P. Tan, SIAM J Optim, 29:2053-2078, 2019) has drawn much attention due to its efficiency in solvin…
Non-convex Pose Graph Optimization in SLAM via Proximal Linearized Riemannian ADMM
Xin Chen, Chunfeng Cui, Deren Han +1
Pose graph optimization (PGO) is a well-known technique for solving the pose-based simultaneous localization and mapping (SLAM) problem. In this paper, we represent the rotation an…
Inertial Accelerated Stochastic Mirror Descent for Large-Scale Generalized Tensor CP Decomposition
Zehui Liu, Qingsong Wang, Chunfeng Cui +1
The majority of classic tensor CP decomposition models are designed for squared loss, employing Euclidean distance as a local proximal term. However, the Euclidean distance is unsu…
A Momentum Accelerated Algorithm for ReLU-based Nonlinear Matrix Decomposition
Qingsong Wang, Chunfeng Cui, Deren Han
Recently, there has been a growing interest in the exploration of Nonlinear Matrix Decomposition (NMD) due to its close ties with neural networks. NMD aims to find a low-rank matri…
A Bregman Proximal Stochastic Gradient Method with Extrapolation for Nonconvex Nonsmooth Problems
Qingsong Wang, Zehui Liu, Chunfeng Cui +1
In this paper, we explore a specific optimization problem that involves the combination of a differentiable nonconvex function and a nondifferentiable function. The differentiable…