Math @ Duke
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Publications [#333710] of Hau-Tieng Wu
Papers Published
- Talmon, R; Wu, HT, Latent common manifold learning with alternating diffusion: Analysis and applications,
Applied and Computational Harmonic Analysis, vol. 47 no. 3
(November, 2019),
pp. 848-892, Elsevier BV [doi]
(last updated on 2024/04/17)
Abstract: The analysis of data sets arising from multiple sensors has drawn significant research attention over the years. Traditional methods, including kernel-based methods, are typically incapable of capturing nonlinear geometric structures. We introduce a latent common manifold model underlying multiple sensor observations for the purpose of multimodal data fusion. A method based on alternating diffusion is presented and analyzed; we provide theoretical analysis of the method under the latent common manifold model. To exemplify the power of the proposed framework, experimental results in several applications are reported.
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