Metazscil: A meta-learning approach for generalized zero-shot class incremental learning
Generalized zero-shot learning (GZSL) aims to recognize samples whose categories may
not have been seen at training. Standard GZSL cannot handle dynamic addition of new …
not have been seen at training. Standard GZSL cannot handle dynamic addition of new …
Masked two-channel decoupling framework for incomplete multi-view weak multi-label learning
Multi-view learning has become a popular research topic in recent years, but research on
the cross-application of classic multi-label classification and multi-view learning is still in its …
the cross-application of classic multi-label classification and multi-view learning is still in its …
Feature relevance and redundancy coefficients for multi-view multi-label feature selection
Q Han, L Hu, W Gao - Information Sciences, 2024 - Elsevier
Multi-view and multi-label data offer a comprehensive perspective for learning models, but
dimensionality poses a challenge for feature selection. Existing methods based on …
dimensionality poses a challenge for feature selection. Existing methods based on …
[PDF][PDF] Common-individual semantic fusion for multi-view multi-label learning
Abstract In Multi-View Multi-Label Learning, each instance is described by several
heterogeneous features and associated with multiple valid labels simultaneously. Existing …
heterogeneous features and associated with multiple valid labels simultaneously. Existing …
Embedded feature fusion for multi-view multi-label feature selection
With the explosive growth of data sources, multi-view multi-label learning (MVML) has
garnered significant attention. However, the task of selecting informative features in MVML …
garnered significant attention. However, the task of selecting informative features in MVML …
Learning enhanced specific representations for multi-view feature learning
Y Hao, XY Jing, R Chen, W Liu - Knowledge-Based Systems, 2023 - Elsevier
Multi-view data has two basic characteristics: consensus property and complementary
property, in which complementary information refers to all view-specific information. Inspired …
property, in which complementary information refers to all view-specific information. Inspired …
Anchor-guided global view reconstruction for multi-view multi-label feature selection
In multi-view multi-label learning (MVML), the accuracy of feature weights is pivotal for
establishing feature order. However, conventional MVML methods often struggle with …
establishing feature order. However, conventional MVML methods often struggle with …
L-VSM: Label-Driven View-Specific Fusion for Multiview Multilabel Classification
In the task of multiview multilabel (MVML) classification, each instance is represented by
several heterogeneous features and associated with multiple semantic labels. Existing …
several heterogeneous features and associated with multiple semantic labels. Existing …
Decoupled representation for multi-view learning
S Sun, B Wang, Y Tian - Pattern Recognition, 2024 - Elsevier
Learning multi-view data is a central topic for advanced deep model applications. Existing
efforts mainly focus on exploring shared information to maximize the consensus among all …
efforts mainly focus on exploring shared information to maximize the consensus among all …
Align While Fusion: A Generalized Nonaligned Multiview Multilabel Classification Method
Q Zhong, G Lyu, Z Yang - IEEE Transactions on Neural …, 2024 - ieeexplore.ieee.org
In the task of multiview multilabel (MVML) classification, each object is described by several
heterogeneous view features and annotated with multiple relevant labels. Existing MVML …
heterogeneous view features and annotated with multiple relevant labels. Existing MVML …