Clustering is an important unsupervised learning problem in machine learning and statistics. Among many existing algorithms, kernel k-means has drawn much.

Authors. Bowei Yan, Purnamrita Sarkar. Abstract. Clustering is an important unsupervised learning problem in machine learning and statistics.

Jun 6, 2016 · Abstract:Clustering is one of the most important unsupervised problems in machine learning and statistics. Among many existing algorithms, ...

This paper evaluates the robustness of two types of unsupervised learning methods, which work in feature spaces induced by a kernel function, kernel k-means ...

Dec 2, 2016 · Abstract. Clustering is an important unsupervised learning problem in machine learning and statistics. Among many existing algorithms, ...

7 days ago · This paper evaluates the robustness of two types of unsupervised learning methods, which work in feature spaces induced by a kernel function ...

A semidefinite programming relaxation is introduced for the kernel clustering problem and it is proved that under a suitable model specification, ...

This paper shows that in the context of kernel clustering, an SDP relaxation provides strong consistency and better performance with respect to outliers when ...

Request PDF | On Robustness of Kernel Clustering | Clustering is one of the most important unsupervised problems in machine learning and statistics.

Abstract. This paper evaluates the robustness of two types of unsupervised learn- ing methods, which work in feature spaces induced by a kernel function, ...