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Disentangled representation learning for multi-view clustering via von Mises-Fisher hyperspherical embedding

Author(s): Li Z; Luo Z; Bouguila N; Su W; Fan W;

Multi-view clustering has gained significant attention due to its ability to integrate data from diverse perspectives, frequently outperforming single-view approaches. However, existing methods often assume a Gaussian distribution within the latent embedding space, which can degrade performance when handling high-dimensional data or data with complex, non ...

Article GUID: 40664160


Cross-collection latent Beta-Liouville allocation model training with privacy protection and applications

Author(s): Luo Z; Amayri M; Fan W; Bouguila N;

Cross-collection topic models extend previous single-collection topic models, such as Latent Dirichlet Allocation (LDA), to multiple collections. The purpose of cross-collection topic modeling is to model document-topic representations and reveal similarities between each topic and differences among groups. However, the restriction of Dirichlet prior and ...

Article GUID: 36685642


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