8 citations · 8 across the 13 of their papers we have counts for
8 papers · 1 filter
An Alternating Minimization Algorithm for Federated Sparse Orthogonal Nonnegative Matrix Factorization
Yanjiao Zhu, Xianchao Xiu, Yongyang Xiong +1
In this paper, we develop an alternating minimization algorithm for federated sparse orthogonal nonnegative matrix factorization (ONMF) with emphases on controlling client drift. T…
Learning to Select Features with Manifold Deep Unfolding PCA
Jingjing Liu, Pei Tai, Xianchao Xiu +1
Unsupervised feature selection (UFS) is of great significance in image processing and pattern recognition. Nevertheless, existing model-based methods often rely on manually tuned h…
PICANet: Physics-Informed Cascaded Asymmetric Network for Infrared Small Target Detection
Jingjing Liu, Yinchao Han, Xianchao Xiu +2
Infrared small target detection (ISTD) is an important research direction in image processing. However, existing methods are limited by severe background noise propagation and targ…
OptGraph: Large Language Models Enhanced Evolutionary Optimization Via Graph Retrieval-Augmented Generation
Xianchao Xiu, Jianhao Li, Huangyue Chen +1
Large language models (LLMs) have emerged as a powerful tool for automated evolutionary optimization, but existing methods remain limited in pattern reuse, error-aware refinement,…
Vehicle Routing Problem Meets Large Language Models: An Overview and Perspectives
Xianchao Xiu, Chong Shen, Yanjiao Zhu +1
The vehicle routing problem (VRP) is a central optimization problem in artificial intelligence, logistics automation, transportation scheduling, and industrial decision-making. VRP…
Large Language Models for Operations Research: A Comprehensive Survey
Xianchao Xiu, Jianhao Li, Jun Fan +1
Operations Research (OR) serves as a core decision-support methodology for complex systems, with significant applications across mathematics, management science, and computer scien…
Compressed Proximal Federated Learning for Non-Convex Composite Optimization on Heterogeneous Data
Pu Qiu, Chen Ouyang, Yongyang Xiong +3
Federated Composite Optimization (FCO) has emerged as a promising framework for training models with structural constraints (e.g., sparsity) in distributed edge networks. However,…
Efficient Personalized Federated PCA with Manifold Optimization for IoT Anomaly Detection
Xianchao Xiu, Chenyi Huang, Wei Zhang +1
Internet of things (IoT) networks face increasing security threats due to their distributed nature and resource constraints. Although federated learning (FL) has gained prominence…