mlsanityData to 7 Oct 2026

Reactive Soft Prototype Computing for Concept Drift Streams

arXiv 2007.05432 ↗First posted 10 Jul 2020cs.LG stat.MLcited by 39

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Abstract (arXiv)

The amount of real-time communication between agents in an information system has increased rapidly since the beginning of the decade. This is because the use of these systems, e. g. social media, has become commonplace in today's society. This requires analytical algorithms to learn and predict this stream of information in real-time. The nature of these systems is non-static and can be explained, among other things, by the fast pace of trends. This creates an environment in which algorithms must recognize changes and adapt. Recent work shows vital research in the field, but mainly lack stable performance during model adaptation. In this work, a concept drift detection strategy followed by a prototype-based adaptation strategy is proposed. Validated through experimental results on a variety of typical non-static data, our solution provides stable and quick adjustments in times of change.

Key facts. Cited by 39 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Jul 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 8; 2023: 4; 2024: 11; 2025: 6; 2026: 7.

39 papers.

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  1. 2021Detecting Concept Drift With Neural Network Model Uncertaintycited by 21
  2. 2024Online Drift Detection with Maximum Concept Discrepancycited by 12
  3. 2023A comprehensive analysis of concept drift locality in data streamscited by 10
  4. 2021LEAF: Navigating Concept Drift in Cellular Networkscited by 9
  5. 2024Early Concept Drift Detection via Prediction Uncertaintycited by 8
  6. 2025When to retrain a machine learning modelcited by 8
  7. 2023Cost-Effective Retraining of Machine Learning Modelscited by 7
  8. 2023One or Two Things We know about Concept Drift -- A Survey on Monitoring Evolving Environmentscited by 7
  9. 2022Fast & Furious: Modelling Malware Detection as Evolving Data Streamscited by 6
  10. 2022Autoregressive based Drift Detection Methodcited by 4
  11. 2024Identifying Predictions That Influence the Future: Detecting Performative Concept Drift in Data Streamscited by 3
  12. 2024FLAME: Adaptive and Reactive Concept Drift Mitigation for Federated Learning Deploymentscited by 2
27 more
  1. 2025TRACE: A Generalizable Drift Detector for Streaming Data-Driven Optimizationcited by 2
  2. 2021Domain Specific Concept Drift Detectors for Predicting Financial Time Seriescited by 1
  3. 2022Detecting Concept Drift in the Presence of Sparsity -- A Case Study of Automated Change Risk Assessment Systemcited by 1
  4. 2022Frouros: A Python library for drift detection in machine learning systemscited by 1
  5. 2022LE3D: A Lightweight Ensemble Framework of Data Drift Detectors for Resource-Constrained Devicescited by 1
  6. 2022Phases, Modalities, Temporal and Spatial Locality: Domain Specific ML Prefetcher for Accelerating Graph Analyticscited by 1
  7. 2024A Comprehensive Review of Machine Learning Advances on Data Change: A Cross-Field Perspectivecited by 1
  8. 2024An incremental hybrid adaptive network-based IDS in Software Defined Networks to detect stealth attackscited by 1
  9. 2025Interpretable Model Drift Detectioncited by 1
  10. 2026Online Shift Detection and Conformal Adaptation for Deployed Safety Classifierscited by 1
  11. 2022Implicit Concept Drift Detection for Multi-label Data Streamscited by 0
  12. 2022Precise Change Point Detection using Spectral Drift Detectioncited by 0
  13. 2023An Empirical Study of Uncertainty Estimation Techniques for Detecting Drift in Data Streamscited by 0
  14. 2024Streaming detection of significant delay changes in public transport systemscited by 0
  15. 2024Drift Detection: Introducing Gaussian Split Detectorcited by 0
  16. 2024Detecting Interpretable Subgroup Driftscited by 0
  17. 2024A method to benchmark high-dimensional process drift detectioncited by 0
  18. 2024From XAI to MLOps: Explainable Concept Drift Detection with Profile Drift Detectioncited by 0
  19. 2025Solve Smart, Not Often: Policy Learning for Costly MILP Re-solvingcited by 0
  20. 2025Robust Outlier Detection and Low-Latency Concept Drift Adaptation for Data Stream Regression: A Dual-Channel Architecturecited by 0
  21. 2025OLC-WA: Drift Aware Tuning-Free Online Classification with Weighted Averagecited by 0
  22. 2026DriftGuard: A Hierarchical Framework for Concept Drift Detection and Remediation in Supply Chain Forecastingcited by 0
  23. 2026When to Retrain after Drift: A Data-Only Test of Post-Drift Data Size Sufficiencycited by 0
  24. 2026Learner-based Concept Drift Detection: Analysis and Evaluationcited by 0
  25. 2026Candidate Comparability Before Promotion: Conditional Validation in Adaptive Network Intrusion Detectioncited by 0
  26. 2026Online Change-point Detection for Cooperative Multi-Agent Reinforcement Learningcited by 0
  27. 2026SCCM : Stream Cruise Control Method for Automated Drift Detection and Adaptationcited by 0