A survey on concept drift adaptation

Cited by (1,007)

Items 301–400 of 1,007

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5. A Lightweight Concept Drift Detection Ensemble
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6. Credit card fraud detection strategies with consumer incentives
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8. Mitigating Drift in Time Series Data with Noise Augmentation
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9. Don’t Pay for Validation: Detecting Drifts from Unlabeled data Using Margin Density
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10. Online Learning Model for Handling Different Concept Drifts Using Diverse Ensemble Classifiers on Evolving Data Streams
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11. A heterogeneous online learning ensemble for non-stationary environments
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12. The impact of data difficulty factors on classification of imbalanced and concept drifting data streams
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13. DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation
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14. Model-based explanations of concept drift
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15. Machine Learning Techniques for Sensor-Based Human Activity Recognition with Data Heterogeneity—A Review
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16. Incremental knowledge base construction using DeepDive
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17. A drift detection method based on dynamic classifier selection
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18. Asynchronous dual-pipeline deep learning framework for online data stream classification
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19. Application of Machine Learning in Statistical Process Control Charts: A Survey and Perspective
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20. Evasion Attack and Defense on Machine Learning Models in Cyber-Physical Systems: A Survey
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21. Decomposing time series into deterministic and stochastic influences: A survey
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22. Adaptive online incremental learning for evolving data streams
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23. Tackling Virtual and Real Concept Drifts: An Adaptive Gaussian Mixture Model Approach
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24. Domain Adaptation Mixture of Gaussian Processes for Online Soft Sensor Modeling of Multimode Processes When Sensor Degradation Occurs
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25. Fast & Furious: On the modelling of malware detection as an evolving data stream
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28. Explainability and Interpretability in Concept and Data Drift: A Systematic Literature Review
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29. FEDD: Feature Extraction for Explicit Concept Drift Detection in time series
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30. Robust Prototype-Based Learning on Data Streams
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31. Arbitrage of forecasting experts
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32. Comprehensive Process Drift Detection with Visual Analytics
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34. Amazon SageMaker Model Monitor: A System for Real-Time Insights into Deployed Machine Learning Models
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36. An Adaptive Framework for Multistream Classification
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37. Handling Concept Drift in Predictive Process Monitoring
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38. An Efficient Concept Drift Detection Method for Streaming Data under Limited Labeling
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39. Forecasting in non-stationary environments with fuzzy time series
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40. Internet of Things for Smart Spaces: A University Campus Case Study
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41. Online Learning With Adaptive Rebalancing in Nonstationary Environments
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42. WiFederated: Scalable WiFi Sensing Using Edge-Based Federated Learning
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44. A Dynamic Deep Reinforcement Learning-Bayesian Framework for Anomaly Detection
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45. Hedge Backpropagation Based Online LSTM Architecture for Ultra-Short-Term Wind Power Forecasting
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46. A benchmark and survey of fully unsupervised concept drift detectors on real-world data streams
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47. An approach to handle concept drift in financial time series based on Extreme Learning Machines and explicit Drift Detection
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48. Online Ensemble Using Adaptive Windowing for Data Streams with Concept Drift
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49. Active learning for classifying data streams with unknown number of classes
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50. Evolving rule-based classifiers with genetic programming on GPUs for drifting data streams
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51. Evolving clustering algorithm based on mixture of typicalities for stream data mining
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52. Adaptive performance anomaly detection for online service systems via pattern sketching
    Chen, Zhuangbin, Liu, Jinyang, Su, Yuxin, Zhang, Hongyu, Ling, Xiao, Yang, Yongqiang, Lyu, Michael R. · 2022 · Proceedings of the 44th International Conference on Software Engineering
53. Diversity measure as a new drift detection method in data streaming
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54. Recurring and Novel Class Detection Using Class-Based Ensemble for Evolving Data Stream
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55. DeepDive: A Data Management System for Automatic Knowledge Base Construction
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56. DetectA: abrupt concept drift detection in non-stationary environments
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57. Tackling heterogeneous concept drift with the Self-Adjusting Memory (SAM)
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58. BRIGHT—Drift-Aware Demand Predictions for Taxi Networks
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59. PAC: a novel self-adaptive neuro-fuzzy controller for micro aerial vehicles
    Ferdaus, M.M., Pratama, M., Anavatti, S.G., Garratt, M.A., Lughofer, E. · 2020 · UniSA Research Outputs Repository (University of South Australia)
60. Modeling and mitigating human annotation errors to design efficient stream processing systems with human-in-the-loop machine learning
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62. Three-layer concept drifting detection in text data streams
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63. Threaded ensembles of autoencoders for stream learning
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64. Moving Vehicle Classification Using Wireless Acoustic Sensor Networks
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65. On the Parzen Kernel-Based Probability Density Function Learning Procedures Over Time-Varying Streaming Data With Applications to Pattern Classification
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66. Drifted Twitter Spam Classification Using Multiscale Detection Test on K-L Divergence
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67. Accurate detecting concept drift in evolving data streams
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68. Evaluation Goals for Online Process Mining: A Concept Drift Perspective
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69. Survey on RNN and CRF models for de-identification of medical free text
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70. HistoSketch: Fast Similarity-Preserving Sketching of Streaming Histograms with Concept Drift
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71. Wind power forecasting using ensemble learning for day-ahead energy trading
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72. Domain Aggregation Networks for Multi-Source Domain Adaptation
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73. Incremental learning strategies for credit cards fraud detection
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75. Cost-Effective Incremental Deep Model: Matching Model Capacity With the Least Sampling
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80. Big Data Stream Learning with SAMOA
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92. Robust Drift Characterization from Event Streams of Business Processes
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