منابع مشابه
Sketched Clustering via Hybrid Approximate Message Passing
In sketched clustering, the dataset is first sketched down to a vector of modest size, from which the cluster centers are subsequently extracted. The goal is to perform clustering more efficiently than with methods that operate on the full training data, such as k-means++. For the sketching methodology recently proposed by Keriven, Gribonval, et al., which can be interpreted as a random samplin...
متن کاملSubspace Clustering
Data structure analysis is an important basis of machine learning and data science, which is now widely used in computational visualization problems, e.g. facial recognition, image classification, and motion segmentation. In this project, I would like to deal with a set of small classification problems and use methods like PCA, spectral analysis, kmanifold, etc. By exploring different methods, ...
متن کاملClustering Consistent Sparse Subspace Clustering
Subspace clustering is the problem of clustering data points into a union of lowdimensional linear/affine subspaces. It is the mathematical abstraction of many important problems in computer vision, image processing and machine learning. A line of recent work [4, 19, 24, 20] provided strong theoretical guarantee for sparse subspace clustering [4], the state-of-the-art algorithm for subspace clu...
متن کاملFuzzy Subspace Clustering
In clustering we often face the situation that only a subset of the available attributes is relevant for forming clusters, even though this may not be known beforehand. In such cases it is desirable to have a clustering algorithm that automatically weights attributes or even selects a proper subset. In this paper I study such an approach for fuzzy clustering, which is based on the idea to trans...
متن کاملSubspace K-means clustering.
To achieve an insightful clustering of multivariate data, we propose subspace K-means. Its central idea is to model the centroids and cluster residuals in reduced spaces, which allows for dealing with a wide range of cluster types and yields rich interpretations of the clusters. We review the existing related clustering methods, including deterministic, stochastic, and unsupervised learning app...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Signal Processing
سال: 2018
ISSN: 1053-587X,1941-0476
DOI: 10.1109/tsp.2017.2781649