Finding Frequent Entities in Continuous Data

• Published in: arXiv.org
• Main Authors: Alet, Ferran, Chitnis, Rohan, Kaelbling, Leslie P, Lozano-Perez, Tomas
• Format: Paper
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 08.05.2018
• Subjects: Algorithms; Clustering; Domains; Target markets

In many applications that involve processing high-dimensional data, it is important to identify a small set of entities that account for a significant fraction of detections. Rather than formalize this as a clustering problem, in which all detections must be grouped into hard or soft categories, we...