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[2602.19790] Drift Localization using Conformal Predictions
Summary
This article presents a novel approach to drift localization using conformal predictions, addressing challenges in monitoring concept drift in machine learning systems.
Why It Matters
Understanding and localizing concept drift is crucial for maintaining the performance of machine learning models over time. This research offers a new methodology that could enhance the reliability of these systems, particularly in high-dimensional settings where traditional methods struggle.
Key Takeaways
- Concept drift poses significant challenges for learning systems.
- Traditional local testing methods often fail in high-dimensional contexts.
- The proposed conformal prediction approach shows improved performance on image datasets.
Computer Science > Machine Learning arXiv:2602.19790 (cs) [Submitted on 23 Feb 2026] Title:Drift Localization using Conformal Predictions Authors:Fabian Hinder, Valerie Vaquet, Johannes Brinkrolf, Barbara Hammer View a PDF of the paper titled Drift Localization using Conformal Predictions, by Fabian Hinder and 3 other authors View PDF HTML (experimental) Abstract:Concept drift -- the change of the distribution over time -- poses significant challenges for learning systems and is of central interest for monitoring. Understanding drift is thus paramount, and drift localization -- determining which samples are affected by the drift -- is essential. While several approaches exist, most rely on local testing schemes, which tend to fail in high-dimensional, low-signal settings. In this work, we consider a fundamentally different approach based on conformal predictions. We discuss and show the shortcomings of common approaches and demonstrate the performance of our approach on state-of-the-art image datasets. Comments: Subjects: Machine Learning (cs.LG); Machine Learning (stat.ML) Cite as: arXiv:2602.19790 [cs.LG] (or arXiv:2602.19790v1 [cs.LG] for this version) https://doi.org/10.48550/arXiv.2602.19790 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Fabian Hinder [view email] [v1] Mon, 23 Feb 2026 12:46:50 UTC (179 KB) Full-text links: Access Paper: View a PDF of the paper titled Drift Localization using Conformal Predictions...
