Supplementary Material: A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers of High-dimensional Data
نویسندگان
چکیده
Theorem 1. Let ≤ 1/(6m) be a parameter to control the success probability. Assume
منابع مشابه
A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers of High-dimensional Data
Learning a statistical model for high-dimensional data is an important topic in machine learning. Although this problem has been well studied in the supervised setting, little is known about its unsupervised counterpart. In this work, we focus on the problem of clustering high-dimensional data with sparse centers. In particular, we address the following open question in unsupervised learning: “...
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