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Anjin Liu
Anjin Liu
Decision Systems & E-Service Intelligence Research Laboratory, AAII, University of Technology Sydney
Verified email at uts.edu.au
Title
Cited by
Cited by
Year
Learning under concept drift: A review
J Lu, A Liu, F Dong, F Gu, J Gama, G Zhang
IEEE transactions on knowledge and data engineering 31 (12), 2346-2363, 2018
13042018
Accumulating regional density dissimilarity for concept drift detection in data streams
A Liu, J Lu, F Liu, G Zhang
Pattern Recognition 76, 256-272, 2018
1222018
Regional Concept Drift Detection and Density Synchronized Drift Adaptation
A Liu, Y Song, G Zhang, J Lu
Proceedings of the Twenty-sixth International Joint Conference on Artificialá…, 2017
1092017
Fuzzy time windowing for gradual concept drift adaptation
A Liu, G Zhang, J Lu
2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-6, 2017
832017
Confident anchor-induced multi-source free domain adaptation
J Dong, Z Fang, A Liu, G Sun, T Liu
Advances in Neural Information Processing Systems 34, 2848-2860, 2021
762021
Concept drift detection via equal intensity k-means space partitioning
A Liu, J Lu, G Zhang
IEEE transactions on cybernetics 51 (6), 3198-3211, 2020
762020
Data-driven decision support under concept drift in streamed big data
J Lu, A Liu, Y Song, G Zhang
Complex & intelligent systems 6 (1), 157-163, 2020
682020
Learning bounds for open-set learning
Z Fang, J Lu, A Liu, F Liu, G Zhang
International conference on machine learning, 3122-3132, 2021
532021
Diverse instance-weighting ensemble based on region drift disagreement for concept drift adaptation
A Liu, J Lu, G Zhang
IEEE transactions on neural networks and learning systems 32 (1), 293-307, 2020
502020
A segment-based drift adaptation method for data streams
Y Song, J Lu, A Liu, H Lu, G Zhang
IEEE transactions on neural networks and learning systems 33 (9), 4876-4889, 2021
242021
Elastic gradient boosting decision tree with adaptive iterations for concept drift adaptation
K Wang, J Lu, A Liu, Y Song, L Xiong, G Zhang
Neurocomputing 491, 288-304, 2022
222022
Real-time prediction system of train carriage load based on multi-stream fuzzy learning
H Yu, J Lu, A Liu, B Wang, R Li, G Zhang
IEEE Transactions on Intelligent Transportation Systems 23 (9), 15155-15165, 2022
212022
Concept drift detection: Dealing with missing values via fuzzy distance estimations
A Liu, J Lu, G Zhang
IEEE Transactions on Fuzzy Systems 29 (11), 3219-3233, 2020
192020
Concept drift detection delay index
A Liu, J Lu, Y Song, J Xuan, G Zhang
IEEE Transactions on Knowledge and Data Engineering 35 (5), 4585-4597, 2022
162022
Evolving gradient boost: A pruning scheme based on loss improvement ratio for learning under concept drift
K Wang, J Lu, A Liu, G Zhang, L Xiong
IEEE Transactions on Cybernetics 53 (4), 2110-2123, 2021
152021
Concept drift detection based on anomaly analysis
A Liu, G Zhang, J Lu
Neural Information Processing: 21st International Conference, ICONIP 2014á…, 2014
92014
Real-time decision making for train carriage load prediction via multi-stream learning
H Yu, A Liu, B Wang, R Li, G Zhang, J Lu
AI 2020: Advances in Artificial Intelligence: 33rd Australasian Jointá…, 2020
82020
Fast switch Na´ve Bayes to avoid redundant update for concept drift learning
A Liu, G Zhang, K Wang, J Lu
2020 International Joint Conference on Neural Networks (IJCNN), 1-7, 2020
72020
Concept drift adaptation for learning with streaming data
A Liu
42018
Knowledge graph-based entity importance learning for multi-stream regression on Australian fuel price forecasting
D Chow, A Liu, G Zhang, J Lu
2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019
32019
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