A Demonstration of AutoOD: A Self-Tuning Anomaly Detection System
Summary: Demo of AutoOD, an unsupervised self-tuning anomaly detector that eliminates manual model selection. AutoOD matches supervised performance without labels and provides a visual interface to inspect its self-tuning choices and data patterns. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Dennis Hofmann
- 2. Peter VanNostrand
- 3. Huayi Zhang
- 4. Yizhou Yan
- 5. Lei Cao
- 6. Samuel Madden
- 7. Elke Rundensteiner
Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,455 | AutoOD: Automatic Outlier Detection | 2023 | SIGMOD | 6.1644904e-05 |
| 9,871 | Substructure-aware Log Anomaly Detection | 2025 | VLDB | 4.2626861e-05 |
| 9,983 | Towards Scalable Visual Data Wrangling via Direct Manipulation | 2026 | CIDR | 4.1905499e-05 |
| 10,834 | EasyAD: A Demonstration of Automated Solutions for Time-Series Anomaly Detection | 2025 | VLDB | 4.1905499e-05 |
| 11,011 | MetaStore: Analyzing Deep Learning Meta-Data at Scale | 2024 | VLDB | 4.1905499e-05 |
| 11,293 | ADOps: An Anomaly Detection Pipeline in Structured Logs | 2023 | VLDB | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 159 | LOF: Identifying Density-Based Local Outliers | 2000 | SIGMOD | 0.00040135453 |
| 697 | Efficient Algorithms for Mining Outliers from Large Data Sets | 2000 | SIGMOD | 0.00017964755 |
| 768 | Algorithms for Mining Distance-Based Outliers in Large Datasets | 1998 | VLDB | 0.00016864875 |
| 917 | Democratizing Data Science through Interactive Curation of ML Pipelines | 2019 | SIGMOD | 0.00015324193 |
| 2,129 | MacroBase: Prioritizing Attention in Fast Data | 2017 | SIGMOD | 9.4799835e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,834 | EasyAD: A Demonstration of Automated Solutions for Time-Series Anomaly Detection | 2025 | VLDB | 4.1905499e-05 |
| 4,155 | Robust and Transferable Log-based Anomaly Detection | 2023 | SIGMOD | 6.3970893e-05 |
| 9,477 | OIE: An Interpretable System for Outlier Explanation and Summarization | 2025 | SIGMOD | 4.3300131e-05 |
| 10,578 | Unsupervised Anomaly Detection in Multivariate Time Series across Heterogeneous Domains | 2025 | VLDB | 4.1905499e-05 |
| 6,435 | An Experimental Evaluation of Anomaly Detection in Time Series | 2024 | VLDB | 5.0555305e-05 |
| 10,745 | TSB-AutoAD: Towards Automated Solutions for Time-Series Anomaly Detection | 2025 | VLDB | 4.1905499e-05 |
| 11,293 | ADOps: An Anomaly Detection Pipeline in Structured Logs | 2023 | VLDB | 4.1905499e-05 |
| 11,097 | Time-Series Anomaly Detection: Overview and New Trends | 2024 | VLDB | 4.1905499e-05 |
| 6,419 | AutoTSAD: Unsupervised Holistic Anomaly Detection for Time Series Data | 2024 | VLDB | 5.0621949e-05 |
| 4,455 | AutoOD: Automatic Outlier Detection | 2023 | SIGMOD | 6.1644904e-05 |