Polytree-Augmented Classifier Chains for Multi-Label Classification. - Lu Sun 001; Mineichi Kudo (IJCAI, 2015)

A Scalable Clustering-Based Local Multi-Label Classification Method. - Lu Sun 001; Mineichi Kudo; Keigo Kimura (ECAI, 2016)

Fast random k-labELsets for large-scale multi-label classification. - Keigo Kimura; Mineichi Kudo; Lu Sun 001; Sadamori Koujaku (ICPR, 2016)

Locality in multi-label classification problems. - Batzaya Norov-Erdene; Mineichi Kudo; Lu Sun 001; Keigo Kimura (ICPR, 2016)

Multi-label classification with meta-label-specific features. - Lu Sun 001; Mineichi Kudo; Keigo Kimura (ICPR, 2016)

Simultaneous Nonlinear Label-Instance Embedding for Multi-label Classification. - Keigo Kimura; Mineichi Kudo; Lu Sun 001 (S+SSPR, 2016)

MLC Toolbox: A MATLAB/OCTAVE Library for Multi-Label Classification. - Keigo Kimura; Lu Sun 001; Mineichi Kudo (CoRR, 2017)

READER: Robust Semi-Supervised Multi-Label Dimension Reduction. - Lu Sun 001; Mineichi Kudo; Keigo Kimura (IEICE Trans. Inf. Syst., 2017)

Optimization of classifier chains via conditional likelihood maximization. - Lu Sun 001; Mineichi Kudo (Pattern Recognit., 2018)

Fast and Robust Multi-View Multi-Task Learning via Group Sparsity. - Lu Sun 001; Canh Hao Nguyen; Hiroshi Mamitsuka (IJCAI, 2019)

Multiplicative Sparse Feature Decomposition for Efficient Multi-View Multi-Task Learning. - Lu Sun 001; Canh Hao Nguyen; Hiroshi Mamitsuka (IJCAI, 2019)

Multi-label classification by polytree-augmented classifier chains with label-dependent features. - Lu Sun 001; Mineichi Kudo (Pattern Anal. Appl., 2019)

Multi-Task Personalized Learning with Sparse Network Lasso. - Jiankun Wang 002; Lu Sun 001 (IJCAI, 2022)

Retargeted Regression Methods for Multi-label Learning. - Keigo Kimura; Jiaqi Bao; Mineichi Kudo; Lu Sun 001 (S+SSPR, 2022)

Efficient Leave-One-Out Evaluation of Kernelized Implicit Mappings. - Mineichi Kudo; Keigo Kimura; Shumpei Morishita; Lu Sun 001 (S+SSPR, 2022)

Realization of Autoencoders by Kernel Methods. - Shumpei Morishita; Mineichi Kudo; Keigo Kimura; Lu Sun 001 (S+SSPR, 2022)

CEMENT: Incomplete Multi-View Weak-Label Learning with Long-Tailed Labels. - Zhiwei Li 003; Lu Sun 001; Mineichi Kudo; Kego Kimura (CoRR, 2022)

Structured Sparse Multi-Task Learning with Generalized Group Lasso. - Luhuan Fei; Lu Sun 001; Mineichi Kudo; Keigo Kimura (ECAI, 2023)

Grouped Multi-Task Learning with Hidden Tasks Enhancement. - Jiachun Jin; Jiankun Wang 002; Lu Sun 001; Jie Zheng; Mineichi Kudo (ECAI, 2023)

Multiplicative Sparse Tensor Factorization for Multi-View Multi-Task Learning. - Xinyi Wang; Lu Sun 001; Canh Hao Nguyen; Hiroshi Mamitsuka (ECAI, 2023)

Fed-SC: One-Shot Federated Subspace Clustering over High-Dimensional Data. - Songjie Xie; Youlong Wu; Kewen Liao; Lu Chen 008; Chengfei Liu; Haifeng Shen; MingJian Tang 001; Lu Sun 001 (ICDE, 2023)

Multi-Label Personalized Classification via Exclusive Sparse Tensor Factorization. - Weijia Lin; Jiankun Wang 002; Lu Sun 001; Mineichi Kudo; Keigo Kimura (ICDM, 2023)

Generalized Discriminative Deep Non-Negative Matrix Factorization Based on Latent Feature and Basis Learning. - Zijian Yang; Zhiwei Li 007; Lu Sun 001 (IJCAI, 2023)

Incomplete Multi-view Weak-Label Learning with Noisy Features and Imbalanced Labels. - Zhiwei Li 007; Zijian Yang; Lu Sun 001; Mineichi Kudo; Keigo Kimura (PRICAI (2), 2023)

Partial Multi-label Learning with a Few Accurately Labeled Data. - Haruhi Mizuguchi; Keigo Kimura; Mineichi Kudo; Lu Sun 001 (PRICAI (2), 2023)

Learning Compact Neural Networks via Generalized Structured Sparsity. - Ke Bian; Lu Sun 001; Dengji Zhao (ECAI, 2024)

Learning Low-Rank Tensor Cores with Probabilistic ℓ0-Regularized Rank Selection for Model Compression. - Tianxiao Cao; Lu Sun 001; Canh Hao Nguyen; Hiroshi Mamitsuka (IJCAI, 2024)

MoME: Mixture-of-Masked-Experts for Efficient Multi-Task Recommendation. - Jiahui Xu; Lu Sun 001; Dengji Zhao (SIGIR, 2024)

Robust embedding regression for semi-supervised learning. - Jiaqi Bao; Mineichi Kudo; Keigo Kimura; Lu Sun 001 (Pattern Recognit., 2024)

Redirected transfer learning for robust multi-layer subspace learning. - Jiaqi Bao; Mineichi Kudo; Keigo Kimura; Lu Sun 001 (Pattern Anal. Appl., 2024)

Multi-level sparse network lasso: Locally sparse learning with flexible sample clusters. - Luhuan Fei; Xinyi Wang; Jiankun Wang 002; Lu Sun 001; Yuyao Zhang (Neurocomputing, 2025)

Robust multi-view subspace clustering with missing data by aligning nonlinear manifolds. - Zhan-Wang Mao; Lu Sun 001; Youlong Wu (Pattern Recognit., 2025)

Multi-level network Lasso for multi-task personalized learning. - Jiankun Wang 002; Luhuan Fei; Lu Sun 001 (Pattern Recognit., 2025)

Multi-view multi-label personalized classification via generalized exclusive sparse tensor factorization. - Luhuan Fei; Weijia Lin; Jiankun Wang 002; Lu Sun 001; Mineichi Kudo; Keigo Kimura (Knowl. Inf. Syst., 2025)