Generalized Clustering via Kernel Embeddings

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Kernel Mean Embedding of Distributions: A Review and Beyonds (2016, methodology): “The MMD has been applied extensively in many applications, namely, clustering (Jegelka et al. 2009), density estimation (Song et al. 2007a; 2008), (conditional) independence tests (Fukumizu et al. 2008, Doran et al. 2014, Chwialkowski and Gretton 2014), causal discovery (Sgouritsa et al. 2013, Chen…”
Late Fusion Incomplete Multi-view Clustering (2018, background): “(3) can be obtained by taking the k eigenvectors having the larger eigenvalues of Kb [32].”
Reshaping Visual Datasets for Domain Adaptation (2013, methodology): “Evaluation strategy The four image datasets are commonly used as distinctive domains in research in visual domain adaptation [2, 3, 4, 32].”
Non-Transferable Learning: A New Approach for Model Ownership Verification and Applicability Authorization (2021, background): “…to this theorem and the nature of hard-margin SVM, we can easily obtained that variances σ 0 , σ 1 of P Z | 0 and P Z | 1 are decreasing and the difference between expectations µ 0 and µ 1 is increasing with the saturated increase of MMD, and this conclusion can be found in (Jegelka et al., 2009).”