Jing Li

34 papers A* 3Misc 1Journal 27Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
SCOUT-RAG: Scalable and Cost-Efficient Unifying Traversal for Agentic Graph-RAG over Distributed Domains.
CoRR
Longkun Li, Yuanben Zou, Jinghan Wu, Yuqing Wen, Jing Li, Hangwei Qian, Ivor W. Tsang
2025 J jnl
Alpha and Prejudice: Improving α-Sized Worst Case Fairness via Intrinsic Reweighting.
IEEE Trans. Neural Networks Learn. Syst.
Jing Li, Yinghua Yao, Yuangang Pan, Xuanqian Wang, Ivor W. Tsang, Xiuju Fu
2025 J jnl
Uncover and Unlearn Nuisances: Agnostic Fully Test-Time Adaptation.
CoRR
Ponhvoan Srey, Yaxin Shi, Hangwei Qian, Jing Li, Ivor W. Tsang
2025 J jnl
Uncover and unlearn nuisances: agnostic fully test-time adaptation.
Mach. Learn.
Ponhvoan Srey, Yaxin Shi, Hangwei Qian, Jing Li, Ivor W. Tsang
2024 J jnl
Alpha and Prejudice: Improving α-sized Worst-case Fairness via Intrinsic Reweighting.
CoRR
Jing Li, Yinghua Yao, Yuangang Pan, Xuanqian Wang, Ivor W. Tsang, Xiuju Fu
2024 — conf
Fine-Grained Partial Label Learning.
CAI
Cheng Chen, Yueming Lyu, Xingrui Yu, Jing Li, Ivor W. Tsang
2024 J jnl
Generative Adversarial Ranking Nets.
J. Mach. Learn. Res.
Yinghua Yao, Yuangang Pan, Jing Li, Ivor W. Tsang, Xin Yao
2024 J jnl
Historical Information-Aided Monitoring of Few-Sample Modes in Industrial Processes With Orthogonal Transferred Projection.
IEEE Trans. Ind. Informatics
Kai Wang, Xiang Lei, Wenxuan Zhou, Saige Cheng, Jing Li
2024 J jnl
PROUD: PaRetO-gUided Diffusion Model for Multi-objective Generation.
CoRR
Yinghua Yao, Yuangang Pan, Jing Li, Ivor W. Tsang, Xin Yao
2024 J jnl
PROUD: PaRetO-gUided diffusion model for multi-objective generation.
Mach. Learn.
Yinghua Yao, Yuangang Pan, Jing Li, Ivor W. Tsang, Xin Yao
2024 J jnl
Sanitized clustering against confounding bias.
Mach. Learn.
Yinghua Yao, Yuangang Pan, Jing Li, Ivor W. Tsang, Xin Yao
2024 J jnl
Taming Overconfident Prediction on Unlabeled Data From Hindsight.
IEEE Trans. Neural Networks Learn. Syst.
Jing Li, Yuangang Pan, Ivor W. Tsang
2024 A* conf
Towards Harmless Rawlsian Fairness Regardless of Demographic Prior.
NeurIPS
Xuanqian Wang, Jing Li, Ivor W. Tsang, Yew Soon Ong
2024 J jnl
Towards Harmless Rawlsian Fairness Regardless of Demographic Prior.
CoRR
Xuanqian Wang, Jing Li, Ivor W. Tsang, Yew-Soon Ong
2023 J jnl
Earning Extra Performance From Restrictive Feedbacks.
IEEE Trans. Pattern Anal. Mach. Intell.
Jing Li, Yuangang Pan, Yueming Lyu, Yinghua Yao, Yulei Sui, Ivor W. Tsang
2023 J jnl
Earning Extra Performance from Restrictive Feedbacks.
CoRR
Jing Li, Yuangang Pan, Yueming Lyu, Yinghua Yao, Yulei Sui, Ivor W. Tsang
2023 J jnl
Fairness in graph-based semi-supervised learning.
Knowl. Inf. Syst.
Tao Zhang, Tianqing Zhu, Mengde Han, Fengwen Chen, Jing Li, Wanlei Zhou, Philip S. Yu
2023 J jnl
Implicit Weight Learning for Multi-View Clustering.
IEEE Trans. Neural Networks Learn. Syst.
Feiping Nie, Shaojun Shi, Jing Li, Xuelong Li
2023 J jnl
Revisiting model fairness via adversarial examples.
Knowl. Based Syst.
Tao Zhang, Tianqing Zhu, Jing Li, Wanlei Zhou, Philip S. Yu
2023 J jnl
Sanitized Clustering against Confounding Bias.
CoRR
Yinghua Yao, Yuangang Pan, Jing Li, Ivor W. Tsang, Xin Yao
2022 J jnl
Fairness in Semi-Supervised Learning: Unlabeled Data Help to Reduce Discrimination.
IEEE Trans. Knowl. Data Eng.
Tao Zhang, Tianqing Zhu, Jing Li, Mengde Han, Wanlei Zhou, Philip S. Yu
2021 J jnl
Taming Overconfident Prediction on Unlabeled Data from Hindsight.
CoRR
Jing Li, Yuangang Pan, Ivor W. Tsang
2020 J jnl
Fairness Constraints in Semi-supervised Learning.
CoRR
Tao Zhang, Tianqing Zhu, Mengde Han, Jing Li, Wanlei Zhou, Philip S. Yu
2020 J jnl
Fairness in Semi-supervised Learning: Unlabeled Data Help to Reduce Discrimination.
CoRR
Tao Zhang, Tianqing Zhu, Jing Li, Mengde Han, Wanlei Zhou, Philip S. Yu
2020 J jnl
Secure Metric Learning via Differential Pairwise Privacy.
CoRR
Jing Li, Yuangang Pan, Yulei Sui, Ivor W. Tsang
2020 J jnl
Secure Metric Learning via Differential Pairwise Privacy.
IEEE Trans. Inf. Forensics Secur.
Jing Li, Yuangang Pan, Yulei Sui, Ivor W. Tsang
2019 J jnl
Intrinsic Weight Learning Approach for Multi-view Clustering.
CoRR
Feiping Nie, Jing Li, Xuelong Li
2018 J jnl
Auto-Weighted Multi-View Learning for Image Clustering and Semi-Supervised Classification.
IEEE Trans. Image Process.
Feiping Nie, Guohao Cai, Jing Li, Xuelong Li
2018 Misc conf
Directly Solving the Original Ratiocut Problem for Effective Data Clustering.
ICASSP
Jing Li, Feiping Nie, Xuelong Li
2018 — —
Solid State Drives in modern computing systems.
Jing Li
2017 J jnl
Convex Multiview Semi-Supervised Classification.
IEEE Trans. Image Process.
Feiping Nie, Jing Li, Xuelong Li
2017 — conf
Multi-label Learning with Label-Specific Feature Selection.
ICONIP (1)
Yan Yan, ShiNing Li, Zhe Yang, Xiao Zhang, Jing Li, Anyi Wang, Jingyu Zhang
2017 A* conf
Self-weighted Multiview Clustering with Multiple Graphs.
IJCAI
Feiping Nie, Jing Li, Xuelong Li
2016 A* conf
Parameter-Free Auto-Weighted Multiple Graph Learning: A Framework for Multiview Clustering and Semi-Supervised Classification.
IJCAI
Feiping Nie, Jing Li, Xuelong Li