One or two things we know about concept drift—a survey on monitoring in evolving environments. Part A: detecting concept drift
The world surrounding us is subject to constant change. These changes, frequently
described as concept drift, influence many industrial and technical processes. As they can …
described as concept drift, influence many industrial and technical processes. As they can …
Towards Trustworthy Machine Learning in Production: An Overview of the Robustness in MLOps Approach
Artificial intelligence (AI), and especially its sub-field of Machine Learning (ML), are
impacting the daily lives of everyone with their ubiquitous applications. In recent years, AI …
impacting the daily lives of everyone with their ubiquitous applications. In recent years, AI …
Driftsurf: Stable-state/reactive-state learning under concept drift
A Tahmasbi, E Jothimurugesan… - International …, 2021 - proceedings.mlr.press
When learning from streaming data, a change in the data distribution, also known as
concept drift, can render a previously-learned model inaccurate and require training a new …
concept drift, can render a previously-learned model inaccurate and require training a new …
[HTML][HTML] Model-based explanations of concept drift
Abstract Concept drift refers to the phenomenon that the distribution generating the
observed data changes over time. If drift is present, machine learning models can become …
observed data changes over time. If drift is present, machine learning models can become …
Suitability of different metric choices for concept drift detection
The notion of concept drift refers to the phenomenon that the distribution, which is underlying
the observed data, changes over time; as a consequence machine learning models may …
the observed data, changes over time; as a consequence machine learning models may …
On Sample Selection for Continual Learning: a Video Streaming Case Study
Machine learning (ML) is a powerful tool to model the complexity of communication
networks. As networks evolve, we cannot only train once and deploy. Retraining models …
networks. As networks evolve, we cannot only train once and deploy. Retraining models …
Concept drift detection with quadtree-based spatial mapping of streaming data
RA Coelho, LCB Torres, CL de Castro - Information Sciences, 2023 - Elsevier
Online learning is a complex task, especially when the data stream changes its distribution
over time. It's challenging to monitor and detect these changes to maintain the performance …
over time. It's challenging to monitor and detect these changes to maintain the performance …
One or Two Things We know about Concept Drift--A Survey on Monitoring Evolving Environments
The world surrounding us is subject to constant change. These changes, frequently
described as concept drift, influence many industrial and technical processes. As they can …
described as concept drift, influence many industrial and technical processes. As they can …
One or two things we know about concept drift—a survey on monitoring in evolving environments. Part B: locating and explaining concept drift
In an increasing number of industrial and technical processes, machine learning-based
systems are being entrusted with supervision tasks. While they have been successfully …
systems are being entrusted with supervision tasks. While they have been successfully …
[PDF][PDF] On the Hardness and Necessity of Supervised Concept Drift Detection.
The notion of concept drift refers to the phenomenon that the distribution generating the
observed data changes over time. If drift is present, machine learning models can become …
observed data changes over time. If drift is present, machine learning models can become …