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by B Ghojogh · 2021 · Cited by 89 — Abstract. This is a tutorial and survey paper on kernels, kernel methods, and related fields. We start with reviewing the history of kernels$by R Jenssen · 2008 · Cited by 49 — The contribution of this paper is to provide a new input space analysis of the properties of sum-of-squared-error K-means clustering perform$by V de Silva · 2004 · Cited by 460 — If the landmarks span a lower-dimensional affine subspace, then LMDS recovers the orthogonal projection of the points onto this subspace."by L Zhang · 2013 · Cited by 47 — SDME not only inherits the merits of the sparsity property of affine subspace but also boosts the compactness of intra-manifold, which achieve&by T Li · 2016 · Cited by 113 — Our approach is to introduce network cohesion using penalties built using the network information, and framing the problem as loss plus penalty;+by T Pang · Cited by 21 — In this paper, we propose a novel linear subspace learning algorithm called Flexible Orthogonal. Neighborhood Preserving Embedding (FONPE),.`Mar 3, 2015 — Theorems below show that subspace frames satisfy natural modifications of theorem 1.2.2, equation (1.8), and equation (1.9). Let Won be a set of *