8 citations · 8 across the 13 of their papers we have counts for
9 papers · 1 filter
Data-Adaptive Transformed Bilateral Tensor Low-Rank Representation for Clustering
Hui Chen, Xinjie Wang, Xianchao Xiu +1
Tensor low-rank representation (TLRR) has demonstrated significant success in image clustering. However, most existing methods rely on fixed transformations and suffer from poor ro…
Lightweight Deep Unfolding Networks with Enhanced Robustness for Infrared Small Target Detection
Jingjing Liu, Yinchao Han, Xianchao Xiu +2
Infrared small target detection (ISTD) is one of the key techniques in image processing. Although deep unfolding networks (DUNs) have demonstrated promising performance in ISTD due…
Transformer-Guided Content-Adaptive Graph Learning for Hyperspectral Unmixing
Hui Chen, Liangyu Liu, Xianchao Xiu +1
Hyperspectral unmixing (HU) targets to decompose each mixed pixel in remote sensing images into a set of endmembers and their corresponding abundances. Despite significant progress…
STAR-Net: An Interpretable Model-Aided Network for Remote Sensing Image Denoising
Jingjing Liu, Jiashun Jin, Xianchao Xiu +2
Remote sensing image (RSI) denoising is an important topic in the field of remote sensing. Despite the impressive denoising performance of RSI denoising methods, most current deep…
Robust Sparse Phase Retrieval: Statistical Guarantee, Optimality Theory and Convergent Algorithm
Jun Fan, Ailing Yan, Xianchao Xiu +1
Phase retrieval (PR) is a popular research topic in signal processing and machine learning. However, its performance degrades significantly when the measurements are corrupted by n…
Bi-Level Unsupervised Feature Selection
Jingjing Liu, Xiansen Ju, Xianchao Xiu +1
Unsupervised feature selection (UFS) is an important task in data engineering. However, most UFS methods construct models from a single perspective and often fail to simultaneously…
Sparse Tensor CCA via Manifold Optimization for Multi-View Learning
Yanjiao Zhu, Wanquan Liu, Xianchao Xiu +1
Tensor canonical correlation analysis (TCCA) has garnered significant attention due to its effectiveness in capturing high-order correlations in multi-view learning. However, exist…
Adaptive Multi-Order Graph Regularized NMF with Dual Sparsity for Hyperspectral Unmixing
Hui Chen, Liangyu Liu, Xianchao Xiu +1
Hyperspectral unmixing (HU) is a critical yet challenging task in remote sensing. However, existing nonnegative matrix factorization (NMF) methods with graph learning mostly focus…
Enhancing Unsupervised Feature Selection via Double Sparsity Constrained Optimization
Xianchao Xiu, Anning Yang, Chenyi Huang +2
Unsupervised feature selection (UFS) is widely applied in machine learning and pattern recognition. However, most of the existing methods only consider a single sparsity, which mak…