A survey on concept drift adaptation

UCI Machine Learning Repository

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Dynamic Graph Regularization for Multi-Stream Concept Drift Self-Adaptation

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DriftShield: Autonomous Fraud Detection via Actor-Critic Reinforcement Learning With Dynamic Feature Reweighting

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Optimizing the Parameters of Drift Detection Methods Using a Genetic Algorithm

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Online adaptive decision trees based on concentration inequalities

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Online entropy-based discretization for data streaming classification

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Combination of information entropy and ensemble classification for detecting concept drift in data stream

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Transfer Learning in Non-stationary Environments

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Social-Aware Sequential Modeling of User Interests: A Deep Learning Approach

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Learning concept drift with ensembles of optimum-path forest-based classifiers

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A Critical Review on Adverse Effects of Concept Drift over Machine Learning Classification Models

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Smart Manufacturing and Continuous Improvement and Adaptation of Predictive Models

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GMM-VRD: A Gaussian Mixture Model for Dealing With Virtual and Real Concept Drifts

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Using AntiPatterns to avoid MLOps MistakesPreprint

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Incremental learning of concept drift in Multiple Instance Learning for industrial visual inspection

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Considerations for Quality Control Monitoring of Machine Learning Models in Clinical Practice

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Temporal-Incremental Learning for Android Malware Detection

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Online deep learning’s role in conquering the challenges of streaming data: a survey

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Concept Drift Detection Based on Deep Neural Networks and Autoencoders

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Applying a kernel function on time-dependent data to provide supervised-learning guarantees

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Improving Collaborative Filtering's Rating Prediction Accuracy by Considering Users' Rating Variability

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Real-Time Construction Simulation Coupling a Concrete Temperature Field Interval Prediction Model with Optimized Hybrid-Kernel RVM for Arch Dams

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Concept Drift Adaptation with Incremental–Decremental SVM

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Statistical Drift Detection Ensemble for batch processing of data streams

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An Overview of Wearable Biosensor Systems for Real-Time Substance Use Detection

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PlatoGL: Effective and Scalable Deep Graph Learning System for Graph-enhanced Real-Time Recommendation

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Are Concept Drift Detectors Reliable Alarming Systems? - A Comparative Study

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Data and Model Harmonization Research Challenges in a Nation Wide Digital Twin

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Anomaly Detection of High-Frequency Sensing Data in Transportation Infrastructure Monitoring System Based on Fine-Tuned Model

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iPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios

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Statistical Process Monitoring of Artificial Neural Networks

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A Broad Ensemble Learning System for Drifting Stream Classification

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Automated Deep Learning: Neural Architecture Search Is Not the End

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Online semi-supervised active learning ensemble classification for evolving imbalanced data streams

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Research on adaptive prediction model of rate of penetration under dynamic formation conditions

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Enhancing hourly electricity forecasting using fuzzy cognitive maps with sample entropy

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Dynamic Marketing Uplift Modeling: A Symmetry-Preserving Framework Integrating Causal Forests with Deep Reinforcement Learning for Personalized Intervention Strategies

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Weighted Naïve Bayes Classifier with Forgetting for Drifting Data Streams

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CPF: Concept Profiling Framework for Recurring Drifts in Data Streams

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Bayesian Models of Data Streams with Hierarchical Power Priors

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Model Change Detection With the MDL Principle

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Drift Detection over Non-stationary Data Streams Using Evolving Spiking Neural Networks

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Adaptive learning on mobile network traffic data

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Efficient Ensemble Classification for Multi-Label Data Streams with Concept Drift

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Scaling Multi-Armed Bandit Algorithms

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Analyzing concept drift: A case study in the financial sector

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Extended Autoencoder for Novelty Detection with Reconstruction along Projection Pathway

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Data Science Approaches to Quality Control in Manufacturing: A Review of Problems, Challenges and Architecture

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Synergetic Learning of Heterogeneous Temporal Sequences for Multi-Horizon Probabilistic Forecasting

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Cost‐Sensitive Classification for Evolving Data Streams with Concept Drift and Class Imbalance

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A Network Intrusion Detection System for Concept Drifting Network Traffic Data

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A service‐agnostic method for predicting service metrics in real time

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HEARTDROID—Rule engine for mobile and context‐aware expert systems

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FANCFIS: Fast adaptive neuro-complex fuzzy inference system

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Handling concept drift in deep learning applications for process monitoring

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Uncovering botnets in IoT sensor networks: a hybrid self-organizing maps approach

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Federated Learning Drift Detection: An Empirical Study on the Impact of Concept and Data Drift

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Responsible AI Framework for Autonomous Vehicles: Addressing Bias and Fairness Risks

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Dual Consolidation for Pre-Trained Model-Based Domain-Incremental Learning

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Federated Learning Under Concept Drift: A Systematic Survey of Foundations, Innovations, and Future Research Directions

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Graph neural networks for anomaly detection: a systematic review of dynamic temporal approaches

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Towards a real-time unsupervised estimation of predictive model degradation

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Quantifying the Performance of Adversarial Training on Language Models with Distribution Shifts

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Managing Dataset Shift by Adversarial Validation for Credit Scoring

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Concept drift detection with quadtree-based spatial mapping of streaming data

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Benchmarking Change Detector Algorithms from Different Concept Drift Perspectives

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An Experimental Evaluation of Process Concept Drift Detection

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Detection of Forest Fires through Deep Unsupervised Learning Modeling of Sentinel-1 Time Series

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On the Local Cache Update Rules in Streaming Federated Learning

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DSIL: An Effective Spectrum Prediction Framework Against Spectrum Concept Drift

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Bias correction of significant wave height with LSTM neural networks

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Reacting to different types of concept drift with adaptive and incremental one-class classifiers

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Combining offline and online classifiers for life-long learning

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Mining multi-dimensional concept-drifting data streams using Bayesian network classifiers

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SNCStream+: Extending a high quality true anytime data stream clustering algorithm

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Automatic analysis of audiostreams in the concept drift environment

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Event-Driven Trust Refreshment on Ambient Services

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Mode tracking using multiple data streams

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Fusion architectures for automatic subject indexing under concept drift

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A Behavior-cluster Based Imbalanced Classification Method for Credit Card Fraud Detection

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Concept Drift Adaption for Online Anomaly Detection in Structural Health Monitoring

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MineCap: super incremental learning for detecting and blocking cryptocurrency mining on software-defined networking

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Accuracy weighted diversity-based online boosting

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Handling Concept Drifts in Regression Problems – the Error Intersection Approach

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Data Life Aware Model Updating Strategy for Stream-Based Online Deep Learning

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