mlsanityData to 7 Oct 2026

PAC-Wrap: Semi-Supervised PAC Anomaly Detection

arXiv 2205.10798 ↗First posted 22 May 2022cs.LG math.ST stat.MLcited by 10

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Abstract (arXiv)

Anomaly detection is essential for preventing hazardous outcomes for safety-critical applications like autonomous driving. Given their safety-criticality, these applications benefit from provable bounds on various errors in anomaly detection. To achieve this goal in the semi-supervised setting, we propose to provide Probably Approximately Correct (PAC) guarantees on the false negative and false positive detection rates for anomaly detection algorithms. Our method (PAC-Wrap) can wrap around virtually any existing semi-supervised and unsupervised anomaly detection method, endowing it with rigorous guarantees. Our experiments with various anomaly detectors and datasets indicate that PAC-Wrap is broadly effective.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 12 of its 40 references that are in the map. First posted on arXiv 22 May 2022.

Builds on

12 of 40 references.

References · 12

  1. 2018GANomaly: Semi-Supervised Anomaly Detection via Adversarial Trainingcited by 409
  2. 2018Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholdingcited by 407
  3. 2019Deep Learning for Anomaly Detection: A Surveycited by 357
  4. 2019Deep Semi-Supervised Anomaly Detectioncited by 290
  5. 2019Deep Anomaly Detection with Deviation Networkscited by 152
  6. 2014Toward Supervised Anomaly Detectioncited by 73
  7. 2018Exact and Robust Conformal Inference Methods for Predictive Machine Learning With Dependent Datacited by 64
  8. 2014Regression Conformal Prediction with Nearest Neighbourscited by 59
  9. 2019PAC Confidence Sets for Deep Neural Networks via Calibrated Predictioncited by 59
  10. 2022iDECODe: In-distribution Equivariance for Conformal Out-of-distribution Detectioncited by 27
  11. 2021Merlion: A Machine Learning Library for Time Seriescited by 25
  12. 2020Semi-supervised Anomaly Detection using AutoEncoderscited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 2; 2024: 1; 2025: 5; 2026: 1.

10 papers.

  1. 2025Conformal Inference under High-Dimensional Covariate Shifts via Likelihood-Ratio Regularizationcited by 11
  2. 2022Conformal Frequency Estimation using Discrete Sketched Data with Coverage for Distinct Queriescited by 10
  3. 2023Unsupervised Anomaly Detection with Rejectioncited by 9
  4. 2024Conformal Structured Predictioncited by 9
  5. 2025Probabilistic Stability Guarantees for Feature Attributionscited by 9
  6. 2023SymmPI: Predictive Inference for Data with Group Symmetriescited by 8
  7. 2025Conformal Information Pursuit for Interactively Guiding Large Language Modelscited by 7
  8. 2025Statistical Methods in Generative AIcited by 4
  9. 2025An Encode-then-Decompose Approach to Unsupervised Time Series Anomaly Detection on Contaminated Training Data--Extended Versioncited by 3
  10. 2026How Many Categories Are Enough? Distribution-Free Certification Limits for Few-Shot Anomaly Thresholdscited by 0