This paper introduces a new nonparametric estimation approach that can be used for data that is not necessarily Gaussian distributed. The proposed approach employs the Shr?odinger...
Given a set of data points drawn from multiple low-dimensional linear subspaces of a high-dimensional space, we consider the problem of clustering these points according to the su...
When designing SAMGrid, a project for distributing high-energy physics computations on a grid, we discovered that it was challenging to decide where to place user's jobs. Job...
A. Baranovski, Gabriele Garzoglio, Igor Terekhov, ...
This paper examines a method of clustering within a fully decentralized multi-agent system. Our goal is to group agents with similar objectives or data, as is done in traditional ...
Elth Ogston, Benno J. Overeinder, Maarten van Stee...
K-means is a widely used partitional clustering method. A large amount of effort has been made on finding better proximity (distance) functions for K-means. However, the common c...