Learning Sparse Binary Code for Maximum Inner Product Search. - Changyi Ma; Fangchen Yu; Yueyao Yu; Wenye Li 001 (CIKM, 2021)

Calibrating Distance Metrics Under Uncertainty. - Wenye Li 001; Fangchen Yu (ECML/PKDD (3), 2022)

Metric Nearness Made Practical. - Wenye Li 001; Fangchen Yu; Zichen Ma (AAAI, 2023)

Highly-Efficient Robinson-Foulds Distance Estimation with Matrix Correction. - Fangchen Yu; Rui Bao; Jianfeng Mao; Wenye Li 001 (ECAI, 2023)

From Incompleteness to Unity: A Framework for Multi-view Clustering with Missing Values. - Fangchen Yu; Zhan Shi; Yuqi Ma; Jianfeng Mao; Wenye Li 001 (ICONIP (11), 2023)

Boosting Spectral Clustering on Incomplete Data via Kernel Correction and Affinity Learning. - Fangchen Yu; Runze Zhao; Zhan Shi; Yiwen Lu; Jicong Fan 001; Yicheng Zeng; Jianfeng Mao; Wenye Li 001 (NeurIPS, 2023)

Online estimation of similarity matrices with incomplete data. - Fangchen Yu; Yicheng Zeng; Jianfeng Mao; Wenye Li 001 (UAI, 2023)

FedLF: Layer-Wise Fair Federated Learning. - Zibin Pan; Chi Li; Fangchen Yu; Shuyi Wang; Haijin Wang; Xiaoying Tang 002; Junhua Zhao 001 (AAAI, 2024)

DocReal: Robust Document Dewarping of Real-Life Images via Attention-Enhanced Control Point Prediction. - Fangchen Yu; Yina Xie; Lei Wu; Yafei Wen; Guozhi Wang; Shuai Ren; Xiaoxin Chen 001; Jianfeng Mao; Wenye Li 001 (WACV, 2024)

A Theory-Driven Approach to Inner Product Matrix Estimation for Incomplete Data: An Eigenvalue Perspective. - Fangchen Yu; Yicheng Zeng; Jianfeng Mao; Wenye Li 001 (WWW, 2025)

Balancing the trade-off between global and personalized performance in federated learning. - Zibin Pan; Chi Li; Fangchen Yu; Shuyi Wang; Xiaoying Tang 002; Junhua Zhao 001 (Inf. Sci., 2025)

KAE: Kolmogorov-Arnold Auto-Encoder for Representation Learning. - Fangchen Yu; Ruilizhen Hu; Yidong Lin; Yuqi Ma; Zhenghao Huang; Wenye Li 001 (CoRR, 2025)