Anjin Liu - RankMe

38 papers A* 5B 4Misc 1Journal 22Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Autonomous Concept Drift Threshold Determination. AAAI Pengqian Lu, Jie Lu, Anjin Liu, En Yu, Guangquan Zhang
2025	J	`jnl`	Adaptive Information Fusion-Based Concept Drift Learning for Evolving Multiple Data Streams. IEEE Trans. Knowl. Data Eng. Kun Wang, Jie Lu, Anjin Liu
2025	J	`jnl`	Autonomous Concept Drift Threshold Determination. CoRR Pengqian Lu, Jie Lu, Anjin Liu, En Yu, Guangquan Zhang
2025	A*	`conf`	Early Concept Drift Detection via Prediction Uncertainty. AAAI Pengqian Lu, Jie Lu, Anjin Liu, Guangquan Zhang
2025	J	`jnl`	SPAD: Seven-Source Token Probability Attribution with Syntactic Aggregation for Detecting Hallucinations in RAG. CoRR Pengqian Lu, Jie Lu, Anjin Liu, Guangquan Zhang
2025	J	`jnl`	Tracking Correlations Between Multiple Data Streams Through Evolutionary Regressor Chains. IEEE Trans. Cybern. Bin Zhang, Jie Lu, Anjin Liu, Xin Yao, Guangquan Zhang
2024	J	`jnl`	A self-adaptive ensemble for user interest drift learning. Neurocomputing Kun Wang, Li Xiong, Anjin Liu, Guangquan Zhang, Jie Lu
2024	J	`jnl`	Early Concept Drift Detection via Prediction Uncertainty. CoRR Pengqian Lu, Jie Lu, Anjin Liu, Guangquan Zhang
2024	J	`jnl`	TS-DM: A Time Segmentation-Based Data Stream Learning Method for Concept Drift Adaptation. IEEE Trans. Cybern. Kun Wang, Jie Lu, Anjin Liu, Guangquan Zhang
2023	—	`conf`	An Augmented Learning Approach for Multiple Data Streams Under Concept Drift. AI (1) Kun Wang, Jie Lu, Anjin Liu, Guangquan Zhang
2023	J	`jnl`	Concept Drift Detection Delay Index. IEEE Trans. Knowl. Data Eng. Anjin Liu, Jie Lu, Yiliao Song, Junyu Xuan, Guangquan Zhang
2023	J	`jnl`	Evolving Gradient Boost: A Pruning Scheme Based on Loss Improvement Ratio for Learning Under Concept Drift. IEEE Trans. Cybern. Kun Wang, Jie Lu, Anjin Liu, Guangquan Zhang, Li Xiong
2023	B	`conf`	TCR-M: A Topic Change Recognition-based Method for Data Stream Learning. KES Kun Wang, Jie Lu, Anjin Liu, Guangquan Zhang
2022	J	`jnl`	A Segment-Based Drift Adaptation Method for Data Streams. IEEE Trans. Neural Networks Learn. Syst. Yiliao Song, Jie Lu, Anjin Liu, Haiyan Lu, Guangquan Zhang
2022	Misc	`conf`	An Empirical Study of Fuzzy Decision Tree for Gradient Boosting Ensemble. AI Zhaoqing Liu, Anjin Liu, Guangquan Zhang, Jie Lu
2022	J	`jnl`	Elastic gradient boosting decision tree with adaptive iterations for concept drift adaptation. Neurocomputing Kun Wang, Jie Lu, Anjin Liu, Yiliao Song, Li Xiong, Guangquan Zhang
2022	J	`jnl`	Real-Time Prediction System of Train Carriage Load Based on Multi-Stream Fuzzy Learning. IEEE Trans. Intell. Transp. Syst. Hang Yu, Jie Lu, Anjin Liu, Bin Wang, Ruimin Li, Guangquan Zhang
2021	J	`jnl`	Concept Drift Detection via Equal Intensity k-Means Space Partitioning. IEEE Trans. Cybern. Anjin Liu, Jie Lu, Guangquan Zhang
2021	J	`jnl`	Concept Drift Detection: Dealing With Missing Values via Fuzzy Distance Estimations. IEEE Trans. Fuzzy Syst. Anjin Liu, Jie Lu, Guangquan Zhang
2021	A*	`conf`	Confident Anchor-Induced Multi-Source Free Domain Adaptation. NeurIPS Jiahua Dong, Zhen Fang, Anjin Liu, Gan Sun, Tongliang Liu
2021	J	`jnl`	Diverse Instance-Weighting Ensemble Based on Region Drift Disagreement for Concept Drift Adaptation. IEEE Trans. Neural Networks Learn. Syst. Anjin Liu, Jie Lu, Guangquan Zhang
2021	A*	`conf`	Learning Bounds for Open-Set Learning. ICML Zhen Fang, Jie Lu, Anjin Liu, Feng Liu, Guangquan Zhang
2021	J	`jnl`	Learning Bounds for Open-Set Learning. CoRR Zhen Fang, Jie Lu, Anjin Liu, Feng Liu, Guangquan Zhang
2020	—	`conf`	An Elastic Gradient Boosting Decision Tree for Concept Drift Learning. Australasian Conference on Artificial Intelligence Kun Wang, Anjin Liu, Jie Lu, Guangquan Zhang, Li Xiong
2020	J	`jnl`	Concept Drift Detection via Equal Intensity k-means Space Partitioning. CoRR Anjin Liu, Jie Lu, Guangquan Zhang
2020	J	`jnl`	Concept Drift Detection: Dealing with MissingValues via Fuzzy Distance Estimations. CoRR Anjin Liu, Jie Lu, Guangquan Zhang
2020	J	`jnl`	Diverse Instances-Weighting Ensemble based on Region Drift Disagreement for Concept Drift Adaptation. CoRR Anjin Liu, Jie Lu, Guangquan Zhang
2020	B	`conf`	Fast Switch Naïve Bayes to Avoid Redundant Update for Concept Drift Learning. IJCNN Anjin Liu, Guangquan Zhang, Kun Wang, Jie Lu
2020	J	`jnl`	Learning under Concept Drift: A Review. CoRR Jie Lu, Anjin Liu, Fan Dong, Feng Gu, João Gama, Guangquan Zhang
2020	—	`conf`	Real-Time Decision Making for Train Carriage Load Prediction via Multi-stream Learning. Australasian Conference on Artificial Intelligence Hang Yu, Anjin Liu, Bin Wang, Ruimin Li, Guangquan Zhang, Jie Lu
2019	B	`conf`	Knowledge graph-based entity importance learning for multi-stream regression on Australian fuel price forecasting. IJCNN Dennis Chow, Anjin Liu, Guangquan Zhang, Jie Lu
2019	J	`jnl`	Learning under Concept Drift: A Review. IEEE Trans. Knowl. Data Eng. Jie Lu, Anjin Liu, Fan Dong, Feng Gu, João Gama, Guangquan Zhang
2018	J	`jnl`	Accumulating regional density dissimilarity for concept drift detection in data streams. Pattern Recognit. Anjin Liu, Jie Lu, Feng Liu, Guangquan Zhang
2018	—	`—`	Concept drift adaptation for learning with streaming data Anjin Liu
2017	B	`conf`	Fuzzy time windowing for gradual concept drift adaptation. FUZZ-IEEE Anjin Liu, Guangquan Zhang, Jie Lu
2017	A*	`conf`	Regional Concept Drift Detection and Density Synchronized Drift Adaptation. IJCAI Anjin Liu, Yiliao Song, Guangquan Zhang, Jie Lu
2016	—	`conf`	An Online Competence-Based Concept Drift Detection Algorithm. Australasian Conference on Artificial Intelligence Anjin Liu, Guangquan Zhang, Jie Lu, Ning Lu, Chin-Teng Lin
2014	—	`conf`	Concept Drift Detection Based on Anomaly Analysis. ICONIP (1) Anjin Liu, Guangquan Zhang, Jie Lu