@inproceedings{08a0931685fe4eacad76b34846a308f2,
title = "Ultrametrics and Outlier Identification",
abstract = "Outliers in clustered data are objects that do not fit well into existing clustering structures. Starting from properties of a special product of matrices with non-negative elements we present an algorithm that uses variations of silhouettes of objects to identify outliers relative to a given clustering.",
keywords = "dissimilarities, silhouettes, ultrametrics",
author = "Dan Simovici and Joshua Yee",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 23rd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2021 ; Conference date: 07-12-2021 Through 10-12-2021",
year = "2021",
doi = "10.1109/SYNASC54541.2021.00027",
language = "English",
series = "Proceedings - 2021 23rd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "99--104",
editor = "Carsten Schneider and Mircea Marin and Viorel Negru and Daniela Zaharie",
booktitle = "Proceedings - 2021 23rd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2021",
}