Name
Title | ||
|---|---|---|
A demonstration of the exathlon benchmarking platform for explainable anomaly detection |
Abstract | ||
|---|---|---|
AbstractIn this demo, we introduce Exathlon - a new benchmarking platform for explainable anomaly detection over high-dimensional time series. We designed Exathlon to support data scientists and researchers in developing and evaluating learned models and algorithms for detecting anomalous patterns as well as discovering their explanations. This demo will showcase Exathlon's curated anomaly dataset, novel benchmarking methodology, and end-to-end data science pipeline in action via example usage scenarios. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.14778/3476311.3476355 | Hosted Content |
DocType | Volume | Issue |
Journal | 14 | 12 |
ISSN | Citations | PageRank |
2150-8097 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vincent Jacob | 1 | 1 | 1.70 |
| Fei Song | 2 | 0 | 1.35 |
| Arnaud Stiegler | 3 | 1 | 1.70 |
| Bijan Rad | 4 | 1 | 1.70 |
| Yanlei Diao | 5 | 2234 | 108.95 |
| Nesime Tatbul | 6 | 3415 | 239.74 |