An Overview of Concept Drift Applications

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How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Road Traffic Forecasting: Recent Advances and New Challenges (2018, background): “Concept drift techniques [120] allow an adaptive learning strategy that has recently started being applied to traffic prediction problem.”
Artificial Intelligence and the Implementation Challenge (2019, neutral): “The issue of security transcends any particular use case of ML and includes any applications or analysis that relies on big data more generally.”
Ensemble learning for data stream analysis: A survey (2017, background): “These studies, and more application oriented papers, such as [208], demonstrate that the problem of concept drift has also been recognized and addressed in multiple application areas.”
Trustworthy AI: From Principles to Practices (2021, methodology): “Deployment Anomaly Monitoring [70, 257, 394] Human-AI Interaction [72, 179, 301, 326] Fail-Safe Mechanism [126, 160, 230, 252] Hardware Security [264, 287, 364]”
From Concept Drift to Model Degradation: An Overview on Performance-Aware Drift Detectors (2022, background): “A broad overview of concept drift applications can be found in [14].”