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Rectified Euler k-means and Beyond
To eliminate the deviation, we propose two Rectified Euler k-means methods, i. e., REK1 and REK2, which retain the merits of EulerK while acquire real centroids residing on the mapped space to better characterize the data structures.
Convex Subspace Clustering by Adaptive Block Diagonal Representation
While the latter directly or explicitly imposes the block diagonal structure prior such as block diagonal representation (BDR) to ensure so-desired block diagonalty even if the data is noisy but at the expense of losing the convexity that the former's objective possesses.
A Centroid Auto-Fused Hierarchical Fuzzy c-Means Clustering
Like k-means and Gaussian Mixture Model (GMM), fuzzy c-means (FCM) with soft partition has also become a popular clustering algorithm and still is extensively studied.
