Latent-space Unfolding for MRI Reconstruction
To circumvent the problems caused by prolonged acquisition periods, compressed sensing
MRI enjoys a high usage profile to accelerate the recovery of high-quality images from under …
MRI enjoys a high usage profile to accelerate the recovery of high-quality images from under …
PGIUN: Physics-Guided Implicit Unrolling Network for Accelerated MRI
To cope with the challenges stemming from prolonged acquisition periods, compressed
sensing MRI has emerged as a popular technique to accelerate the reconstruction of high …
sensing MRI has emerged as a popular technique to accelerate the reconstruction of high …
Semi-supervised pivotal-aware nonnegative matrix factorization with label and pairwise constraint propagation for data clustering
Semi-supervised nonnegative matrix factorization (NMF) methods have found extensive
utility in data clustering applications. However, these existing methods encounter challenges …
utility in data clustering applications. However, these existing methods encounter challenges …
GRESS: Grouping Belief-Based Deep Contrastive Subspace Clustering
The self-expressive coefficient plays a crucial role in the self-expressiveness-based
subspace clustering method. To enhance the precision of the self-expressive coefficient, we …
subspace clustering method. To enhance the precision of the self-expressive coefficient, we …
Self-representative kernel concept factorization
Kernel concept factorization (KCF) has successfully utilized kernel trick to conduct matrix
factorization in the kernel space. However, conventional KCF methods usually define kernel …
factorization in the kernel space. However, conventional KCF methods usually define kernel …
Robust sparse concept factorization with graph regularization for subspace learning
X Hu, D Xiong, L Chai - Digital Signal Processing, 2024 - Elsevier
Abstract Concept factorization (CF) is a powerful tool in subspace learning. Recently graph-
based CF and local coordinate CF have been proposed to exploit the intrinsic geometrical …
based CF and local coordinate CF have been proposed to exploit the intrinsic geometrical …
Robust multi-view clustering via structure regularization concept factorization
X Hu, D Xiong, L Chai - Digital Signal Processing, 2024 - Elsevier
Recently, many concept factorization-based multi-view clustering methods have been
proposed and achieved promising results on text multi-view data. However, existing …
proposed and achieved promising results on text multi-view data. However, existing …
Concept factorization with adaptive graph learning on Stiefel manifold
X Hu, D Xiong, L Chai - Applied Intelligence, 2024 - Springer
In machine learning and data mining, concept factorization (CF) has achieved great success
for its powerful capability in data representation. To learn an adaptive inherent graph …
for its powerful capability in data representation. To learn an adaptive inherent graph …