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2020 – today
- 2024
[j12]Kun Wang, Li Xiong, Anjin Liu, Guangquan Zhang, Jie Lu:
A self-adaptive ensemble for user interest drift learning. Neurocomputing 577: 127308 (2024)- [j11]Kun Wang
, Jie Lu, Anjin Liu, Guangquan Zhang:
TS-DM: A Time Segmentation-Based Data Stream Learning Method for Concept Drift Adaptation. IEEE Trans. Cybern. 54(10): 6000-6011 (2024) - 2023
- [j10]Kun Wang, Jie Lu, Anjin Liu, Guangquan Zhang, Li Xiong:
Evolving Gradient Boost: A Pruning Scheme Based on Loss Improvement Ratio for Learning Under Concept Drift. IEEE Trans. Cybern. 53(4): 2110-2123 (2023) - [j9]Anjin Liu, Jie Lu, Yiliao Song, Junyu Xuan, Guangquan Zhang:
Concept Drift Detection Delay Index. IEEE Trans. Knowl. Data Eng. 35(5): 4585-4597 (2023) - [c13]Kun Wang, Jie Lu, Anjin Liu, Guangquan Zhang:
An Augmented Learning Approach for Multiple Data Streams Under Concept Drift. AI (1) 2023: 391-402 - [c12]Kun Wang, Jie Lu, Anjin Liu, Guangquan Zhang:
TCR-M: A Topic Change Recognition-based Method for Data Stream Learning. KES 2023: 3001-3010 - 2022
- [j8]Kun Wang, Jie Lu, Anjin Liu, Yiliao Song, Li Xiong, Guangquan Zhang:
Elastic gradient boosting decision tree with adaptive iterations for concept drift adaptation. Neurocomputing 491: 288-304 (2022) - [j7]Hang Yu, Jie Lu, Anjin Liu, Bin Wang, Ruimin Li, Guangquan Zhang:
Real-Time Prediction System of Train Carriage Load Based on Multi-Stream Fuzzy Learning. IEEE Trans. Intell. Transp. Syst. 23(9): 15155-15165 (2022) - [j6]Yiliao Song, Jie Lu, Anjin Liu, Haiyan Lu, Guangquan Zhang:
A Segment-Based Drift Adaptation Method for Data Streams. IEEE Trans. Neural Networks Learn. Syst. 33(9): 4876-4889 (2022) - [c11]Zhaoqing Liu, Anjin Liu, Guangquan Zhang, Jie Lu:
An Empirical Study of Fuzzy Decision Tree for Gradient Boosting Ensemble. AI 2022: 716-727 - 2021
- [j5]Anjin Liu, Jie Lu, Guangquan Zhang:
Concept Drift Detection via Equal Intensity k-Means Space Partitioning. IEEE Trans. Cybern. 51(6): 3198-3211 (2021) - [j4]Anjin Liu, Jie Lu, Guangquan Zhang:
Concept Drift Detection: Dealing With Missing Values via Fuzzy Distance Estimations. IEEE Trans. Fuzzy Syst. 29(11): 3219-3233 (2021) - [j3]Anjin Liu, Jie Lu, Guangquan Zhang:
Diverse Instance-Weighting Ensemble Based on Region Drift Disagreement for Concept Drift Adaptation. IEEE Trans. Neural Networks Learn. Syst. 32(1): 293-307 (2021) - [c10]Zhen Fang, Jie Lu, Anjin Liu, Feng Liu, Guangquan Zhang:
Learning Bounds for Open-Set Learning. ICML 2021: 3122-3132 - [c9]Jiahua Dong, Zhen Fang, Anjin Liu, Gan Sun, Tongliang Liu:
Confident Anchor-Induced Multi-Source Free Domain Adaptation. NeurIPS 2021: 2848-2860 - [i5]Zhen Fang, Jie Lu, Anjin Liu, Feng Liu, Guangquan Zhang:
Learning Bounds for Open-Set Learning. CoRR abs/2106.15792 (2021) - 2020
- [c8]Hang Yu, Anjin Liu, Bin Wang, Ruimin Li, Guangquan Zhang, Jie Lu:
Real-Time Decision Making for Train Carriage Load Prediction via Multi-stream Learning. Australasian Conference on Artificial Intelligence 2020: 29-41 - [c7]Kun Wang, Anjin Liu, Jie Lu, Guangquan Zhang, Li Xiong:
An Elastic Gradient Boosting Decision Tree for Concept Drift Learning. Australasian Conference on Artificial Intelligence 2020: 420-432 - [c6]Anjin Liu, Guangquan Zhang, Kun Wang, Jie Lu:
Fast Switch Naïve Bayes to Avoid Redundant Update for Concept Drift Learning. IJCNN 2020: 1-7 - [i4]Jie Lu, Anjin Liu, Fan Dong, Feng Gu, João Gama, Guangquan Zhang:
Learning under Concept Drift: A Review. CoRR abs/2004.05785 (2020) - [i3]Anjin Liu, Jie Lu, Guangquan Zhang:
Diverse Instances-Weighting Ensemble based on Region Drift Disagreement for Concept Drift Adaptation. CoRR abs/2004.05810 (2020) - [i2]Anjin Liu, Jie Lu, Guangquan Zhang:
Concept Drift Detection via Equal Intensity k-means Space Partitioning. CoRR abs/2004.11587 (2020) - [i1]Anjin Liu, Jie Lu, Guangquan Zhang:
Concept Drift Detection: Dealing with MissingValues via Fuzzy Distance Estimations. CoRR abs/2008.03662 (2020)
2010 – 2019
- 2019
- [j2]Jie Lu, Anjin Liu, Fan Dong, Feng Gu, João Gama, Guangquan Zhang:
Learning under Concept Drift: A Review. IEEE Trans. Knowl. Data Eng. 31(12): 2346-2363 (2019) - [c5]Dennis Chow, Anjin Liu, Guangquan Zhang, Jie Lu:
Knowledge graph-based entity importance learning for multi-stream regression on Australian fuel price forecasting. IJCNN 2019: 1-8 - 2018
- [b1]Anjin Liu:
Concept drift adaptation for learning with streaming data. University of Technology Sydney, Australia, 2018 - [j1]Anjin Liu, Jie Lu, Feng Liu, Guangquan Zhang:
Accumulating regional density dissimilarity for concept drift detection in data streams. Pattern Recognit. 76: 256-272 (2018) - 2017
- [c4]Anjin Liu, Guangquan Zhang, Jie Lu:
Fuzzy time windowing for gradual concept drift adaptation. FUZZ-IEEE 2017: 1-6 - [c3]Anjin Liu, Yiliao Song, Guangquan Zhang, Jie Lu:
Regional Concept Drift Detection and Density Synchronized Drift Adaptation. IJCAI 2017: 2280-2286 - 2016
- [c2]Anjin Liu, Guangquan Zhang, Jie Lu, Ning Lu, Chin-Teng Lin:
An Online Competence-Based Concept Drift Detection Algorithm. Australasian Conference on Artificial Intelligence 2016: 416-428 - 2014
- [c1]Anjin Liu, Guangquan Zhang, Jie Lu:
Concept Drift Detection Based on Anomaly Analysis. ICONIP (1) 2014: 263-270
Coauthor Index
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