Incomplete multi-modal representation learning for Alzheimer's disease diagnosis
Sign Up to like & getrecommendations! Published in 2021 at "Medical image analysis"
DOI: 10.1016/j.media.2020.101953
Abstract: Alzheimers disease (AD) is a complex neurodegenerative disease. Its early diagnosis and treatment have been a major concern of researchers. Currently, the multi-modality data representation learning of this disease is gradually becoming an emerging research… read more here.
Keywords: representation learning; incomplete multi; multi; view ... See more keywords
Incomplete Multi-view Data Learning via Adaptive Embedding and Partial l2,1 Norm Constraints for Parkinson's Disease Diagnosis.
Sign Up to like & getrecommendations! Published in 2025 at "IEEE journal of biomedical and health informatics"
DOI: 10.1109/jbhi.2025.3576786
Abstract: Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by mental abnormalities and motor dysfunction. Its early classification and prediction of clinical scores have been major concerns for researchers. Currently, multi-view data learning has become… read more here.
Keywords: view; view data; partial norm; incomplete multi ... See more keywords
Deep Incomplete Multi-View Clustering via Dynamic Imputation and Triple Alignment With Dual Optimization
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2024.3508785
Abstract: In recent years, Incomplete Multi-View Clustering (IMVC) has become an important and challenging task. Although several methods have been proposed to address IMVC, they still have the following drawbacks: i) Due to the presence of… read more here.
Keywords: view; incomplete multi; dual optimization; view clustering ... See more keywords
High-Order Correlation Preserved Incomplete Multi-View Subspace Clustering
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DOI: 10.1109/tip.2022.3147046
Abstract: Incomplete multi-view clustering aims to exploit the information of multiple incomplete views to partition data into their clusters. Existing methods only utilize the pair-wise sample correlation and pair-wise view correlation to improve the clustering performance… read more here.
Keywords: view; high order; multi view; incomplete multi ... See more keywords
NIM-Nets: Noise-Aware Incomplete Multi-View Learning Networks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2022.3226408
Abstract: Data in real world are usually characterized in multiple views, including different types of features or different modalities. Multi-view learning has been popular in the past decades and achieved significant improvements. In this paper, we… read more here.
Keywords: view; nim nets; view learning; multi view ... See more keywords
Adaptive Feature Projection With Distribution Alignment for Deep Incomplete Multi-View Clustering
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2023.3243521
Abstract: Incomplete multi-view clustering (IMVC) analysis, where some views of multi-view data usually have missing data, has attracted increasing attention. However, existing IMVC methods still have two issues: 1) they pay much attention to imputing or… read more here.
Keywords: incomplete multi; distribution alignment; multi view; feature ... See more keywords
Incomplete Multi-View Clustering With Reconstructed Views
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2021.3112114
Abstract: As one category of important incomplete multi-view clustering methods, subspace based methods seek the common latent representation of incomplete multi-view data by matrix factorization and then partition the latent representation to get clustering results. However,… read more here.
Keywords: reconstructed views; multi view; incomplete multi; view clustering ... See more keywords
Incomplete Multi-View Clustering With Sample-Level Auto-Weighted Graph Fusion
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2022.3171911
Abstract: Incomplete multi-view clustering (IMC) has received considerable attention due to its flexibility in fusing the multi-view information when the view samples are partly missing. However, existing methods seldom consider the affection of the missing samples… read more here.
Keywords: view; sample level; multi view; graph fusion ... See more keywords
Robust Tensor Subspace Learning for Incomplete Multi-View Clustering
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DOI: 10.1109/tkde.2024.3399707
Abstract: Incomplete multi-view clustering has represented a significant role in grouping real images. In this study, a novel robust tensor subspace learning (RTSL) is proposed for incomplete multi-view clustering. Specifically, the missing samples within views are… read more here.
Keywords: view; incomplete multi; tensor; robust tensor ... See more keywords
Latent Structure-Aware View Recovery for Incomplete Multi-View Clustering
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DOI: 10.1109/tkde.2024.3445992
Abstract: Incomplete multi-view clustering (IMVC) presents a significant challenge due to the need for effectively exploring complementary and consistent information within the context of missing views. One promising strategy to tackle this challenge is to recover… read more here.
Keywords: view; information; view recovery; incomplete multi ... See more keywords
Relation-aware Shared Representation Learning for Cancer Prognosis Analysis with Auxiliary Clinical Variables and Incomplete Multi-modality Data.
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on medical imaging"
DOI: 10.1109/tmi.2021.3108802
Abstract: The integrative analysis of complementary phenotype information contained in multi-modality data (e.g., histopathological images and genomic data) has advanced the prognostic evaluation of cancers. However, multi-modality based prognosis analysis confronts two challenges: (1) how to… read more here.
Keywords: incomplete multi; analysis; modality data; modality ... See more keywords