Using Projection Gradient Method to Train Linear Support Vector Machines. - Lingfeng Niu; Yong Shi 001 (Web Intelligence/IAT Workshops, 2010)

Semi-supervised PLSA for Document Clustering. - Lingfeng Niu; Yong Shi 001 (ICDM Workshops, 2010)

A new training method for sequence data. - Lingfeng Niu; Yong Shi 001 (ICCS, 2010)

MSSVM: A Modular Solver for Support Vector Machines. - Lingfeng Niu; Yong Shi 001 (Web Intelligence/IAT Workshops, 2011)

Entity Resolution with Attribute and Connection Graph. - Lingfeng Niu; Jianmin Wu; Yong Shi 001 (ICDM Workshops, 2011)

Parallel algorithm for training multiclass proximal Support Vector Machines. - Lingfeng Niu (Appl. Math. Comput., 2011)

A parallel decomposition algorithm for training multiclass kernel-based vector machines. - Lingfeng Niu; Yaxiang Yuan (Optim. Methods Softw., 2011)

Second-order Mining for Active Collaborative Filtering. - Lingfeng Niu; Jianmin Wu; Yong Shi 001 (ICCS, 2011)

Learning Using Privileged Information with L-1 Support Vector Machine. - Lingfeng Niu; Yong Shi 001; Jianmin Wu (Web Intelligence/IAT Workshops, 2012)

Nonlinear L-1 Support Vector Machines for Learning Using Privileged Information. - Lingfeng Niu; Jianmin Wu (ICDM Workshops, 2012)

Training the max-margin sequence model with the relaxed slack variables. - Lingfeng Niu; Jianmin Wu; Yong Shi 001 (Neural Networks, 2012)

Entity Disambiguation with Textual and Connection Information. - Lingfeng Niu; Jianmin Wu; Yong Shi 001 (ICCS, 2012)

Kernel Based Simple Regularized Multiple Criteria Linear Programs for Binary Classification. - Xi Zhao; Lingfeng Niu; Yong Shi 001 (Web Intelligence/IAT Workshops, 2013)

A Simple Regularized Multiple Criteria Linear Programs for Binary Classification. - Lingfeng Niu; Xi Zhao; Yong Shi 001 (ICCS, 2013)

A Simple Decomposition Alternating Direction Method for Matrix Completion. - Lingfeng Niu; Xi Zhao (ITQM, 2013)

Optimality Conditions and a Smoothing Trust Region Newton Method for NonLipschitz Optimization. - Xiaojun Chen 001; Lingfeng Niu; Yaxiang Yuan (SIAM J. Optim., 2013)

A First-Order Decomposition Algorithm for Training Bound-Constrained Support Vector Machines. - Lingfeng Niu; Xi Zhao; Yong Shi 001 (WI-IAT (1), 2014)

Pedestrian Detection Using Privileged Information. - Zhiquan Qi; Yingjie Tian 001; Lingfeng Niu; Fan Meng; Limeng Cui; Yong Shi 001 (ICDM Workshops, 2015)

Alternating Direction Method of Multipliers for Nonparallel Support Vector Machines. - Xin Shen 003; Lingfeng Niu; Yingjie Tian 001; Yong Shi 001 (ICDM Workshops, 2015)

Large-Scale Linear Support Vector Ordinal Regression Solver. - Yong Shi 001; Huadong Wang; Lingfeng Niu (ICDM Workshops, 2015)

Smoothing Trust Region for Digital Image Restoration. - Ruizhi Zhou; Lingfeng Niu; Zhiquan Qi (WI-IAT (3), 2015)

Kernel based simple regularized multiple criteria linear program for binary classification and regression. - Xi Zhao; Yong Shi 001; Lingfeng Niu (Intell. Data Anal., 2015)

Semi-supervised classification with privileged information. - Zhiquan Qi; Yingjie Tian 001; Lingfeng Niu; Bo Wang 049 (Int. J. Mach. Learn. Cybern., 2015)

Robust Unsupervised Feature Learning from Time-Series. - Jianyu Miao; Yong Shi 001; Lingfeng Niu (WI Workshops, 2016)

Large-scale Nonparallel Support Vector Ordinal Regression Solver. - Huadong Wang; Jianyu Miao; Seyed Mojtaba Hosseini Bamakan; Lingfeng Niu; Yong Shi 001 (ICCS, 2017)

A Feasible Direction Method for Optimization Problem with Orthogonal Constraint in Feature Selection. - Jianyu Miao; Yong Shi 001; Lingfeng Niu (ICDM Workshops, 2017)

Augmented SVM with ordinal partitioning for text classification. - Yong Shi 001; Peijia Li; Lingfeng Niu (WI, 2017)

Support vector machine classifier with truncated pinball loss. - Xin Shen 003; Lingfeng Niu; Zhiquan Qi; Yingjie Tian 001 (Pattern Recognit., 2017)

Nonsmooth Penalized Clustering via ℓp Regularized Sparse Regression. - Lingfeng Niu; Ruizhi Zhou; Yingjie Tian 001; Zhiquan Qi; Peng Zhang 001 (IEEE Trans. Cybern., 2017)

Learning With Label Proportions via NPSVM. - Zhiquan Qi; Bo Wang 049; Fan Meng; Lingfeng Niu (IEEE Trans. Cybern., 2017)

Nonparallel Support Vector Ordinal Regression. - Huadong Wang; Yong Shi 001; Lingfeng Niu; Yingjie Tian 001 (IEEE Trans. Cybern., 2017)

Deep Streaming Graph Representations. - Minglong Lei; Yong Shi 001; Peijia Li; Lingfeng Niu (ICCS (3), 2018)

Kernel Extreme Learning Machine for Learning from Label Proportions. - Hao Yuan; Bo Wang 049; Lingfeng Niu (ICCS (2), 2018)

Compact Deep Neural Networks with ℓ1, 1 and ℓ1, 2 Regularization. - Rongrong Ma; Lingfeng Niu (ICDM Workshops, 2018)

Automatic Chinese Multiple-Choice Question Generation for Human Resource Performance Appraisal. - Pei Quan; Yong Shi 001; Lingfeng Niu; Ying Liu 039; Tianlin Zhang (ITQM, 2018)

The Applications of Stochastic Models in Network Embedding: A Survey. - Minglong Lei; Yong Shi 001; Lingfeng Niu (WI, 2018)

A Survey of Sparse-Learning Methods for Deep Neural Networks. - Rongrong Ma; Lingfeng Niu (WI, 2018)

Diffusion Based Network Embedding. - Yong Shi 001; Minglong Lei; Peng Zhang 001; Lingfeng Niu (CoRR, 2018)

A Novel Large-scale Ordinal Regression Model. - Yong Shi 001; Huadong Wang; Xin Shen 003; Lingfeng Niu (CoRR, 2018)

A fast algorithm for nonsmooth penalized clustering. - Ruizhi Zhou; Xin Shen 003; Lingfeng Niu (Neurocomputing, 2018)

Pedestrian detection based on the privileged information. - Fan Meng; Zhiquan Qi; Yingjie Tian 001; Lingfeng Niu (Neural Comput. Appl., 2018)

Adaboost-LLP: A Boosting Method for Learning With Label Proportions. - Zhiquan Qi; Fan Meng; Yingjie Tian 001; Lingfeng Niu; Yong Shi 001; Peng Zhang 001 (IEEE Trans. Neural Networks Learn. Syst., 2018)

Feature Selection With ℓ2, 1-2 Regularization. - Yong Shi 001; Jianyu Miao; Zhengyu Wang; Peng Zhang 001; Lingfeng Niu (IEEE Trans. Neural Networks Learn. Syst., 2018)

A Brief Survey of Relation Extraction Based on Distant Supervision. - Yong Shi 001; Yang Xiao 017; Lingfeng Niu (ICCS (3), 2019)

Optimization Strategies in Quantized Neural Networks: A Review. - Yuhan Lin; Minglong Lei; Lingfeng Niu (ICDM Workshops, 2019)

Sparse Optimization Based on Non-convex ℓ 1/2 Regularization for Deep Neural Networks. - Anda Tang; Rongrong Ma; Jianyu Miao; Lingfeng Niu (ICDS, 2019)

A Brief Review of Receptive Fields in Graph Convolutional Networks. - Pei Quan; Yong Shi 001; Minglong Lei; Jiaxu Leng; Tianlin Zhang; Lingfeng Niu (WI (Companion), 2019)

Graph-Based Clustering via Group Sparsity and Manifold Regularization. - Jianyu Miao; Tiejun Yang; Junwei Jin 001; Lingfeng Niu (IEEE Access, 2019)

Learning Robust Auto-Encoders With Regularizer for Linearity and Sparsity. - Yong Shi 001; Minglong Lei; Rongrong Ma; Lingfeng Niu (IEEE Access, 2019)

Joint Sparse Regularization for Dictionary Learning. - Jianyu Miao; Heling Cao; Xiao-Bo Jin; Rongrong Ma; Xuan Fei; Lingfeng Niu (Cogn. Comput., 2019)

Transformed 𝓁1 Regularization for Learning Sparse Deep Neural Networks. - Rongrong Ma; Jianyu Miao; Lingfeng Niu; Peng Zhang 001 (CoRR, 2019)

Fast kernel extreme learning machine for ordinal regression. - Yong Shi 001; Peijia Li; Hao Yuan; Jianyu Miao; Lingfeng Niu (Knowl. Based Syst., 2019)

Feature selection with MCP $$^2$$ 2 regularization. - Yong Shi 001; Jianyu Miao; Lingfeng Niu (Neural Comput. Appl., 2019)

Transformed ℓ1 regularization for learning sparse deep neural networks. - Rongrong Ma; Jianyu Miao; Lingfeng Niu; Peng Zhang 001 (Neural Networks, 2019)

Diffusion network embedding. - Yong Shi 001; Minglong Lei; Hong Yang 003; Lingfeng Niu (Pattern Recognit., 2019)

Discrete Embedding for Latent Networks. - Hong Yang 003; Ling Chen 006; Minglong Lei; Lingfeng Niu; Chuan Zhou 001; Peng Zhang 001 (IJCAI, 2020)

GGTAN: Graph Gated Talking-Heads Attention Networks for Traveling Salesman Problem. - Shichao Guo; Yang Xiao 017; Lingfeng Niu (WI/IAT, 2020)

A brief survey on Capsule Network. - Ruiyang Shi; Lingfeng Niu (WI/IAT, 2020)

Feature Selection of Network Data VIA ℓ2, p Regularization. - Ruizhi Zhou; Lingfeng Niu (Cogn. Comput., 2020)

A survey of sparse regularization based compression methods. - Anda Tang; Pei Quan; Lingfeng Niu; Yong Shi 001 (ITQM, 2021)

A brief survey on Computational Gromov-Wasserstein distance. - Lei Zheng; Yang Xiao 017; Lingfeng Niu (ITQM, 2021)

Latent Network Embedding via Adversarial Auto-encoders. - Minglong Lei; Yong Shi 001; Lingfeng Niu (CoRR, 2021)

Multi-task Self-distillation for Graph-based Semi-Supervised Learning. - Yating Ren; Junzhong Ji; Lingfeng Niu; Minglong Lei (CoRR, 2021)

Unsupervised feature selection by non-convex regularized self-representation. - Jianyu Miao; Yuan Ping; Zhensong Chen 001; Xiao-Bo Jin; Peijia Li; Lingfeng Niu (Expert Syst. Appl., 2021)

Unsupervised feature selection for attributed graphs. - Ruizhi Zhou; Lingfeng Niu; Hong Yang 003 (Expert Syst. Appl., 2021)

Anomaly detection in dynamic attributed networks. - Ruizhi Zhou; Qin Zhang 011; Peng Zhang 001; Lingfeng Niu; Xiaodong Lin 004 (Neural Comput. Appl., 2021)

Distant Supervision Relation Extraction via adaptive dependency-path and additional knowledge graph supervision. - Yong Shi 001; Yang Xiao 017; Pei Quan; Minglong Lei; Lingfeng Niu (Neural Networks, 2021)

Document-level relation extraction via graph transformer networks and temporal convolutional networks. - Yong Shi 001; Yang Xiao 017; Pei Quan; Minglong Lei; Lingfeng Niu (Pattern Recognit. Lett., 2021)

Optimization Strategies for Client Drift in Federated Learning: A review. - Yong Shi 001; Yuanying Zhang; Yang Xiao 017; Lingfeng Niu (ITQM, 2022)

Sparse Learning for Neural Networks with A Generalized Sparse Regularization. - Anda Tang; Tongsheng Yao; Lingfeng Niu; Yong Shi 001 (ITQM, 2022)

Optimal Transport Guided Node Classification in Cross Networks. - Lei Zheng; Pei Quan; Minglong Lei; Yang Xiao 017; Lingfeng Niu (ITQM, 2022)

Towards Compact Broad Learning System by Combined Sparse Regularization. - Jianyu Miao; Tiejun Yang; Jun-Wei Jin 001; Lijun Sun; Lingfeng Niu; Yong Shi 001 (Int. J. Inf. Technol. Decis. Mak., 2022)

Latent neighborhood-based heterogeneous graph representation. - Yang Xiao 017; Pei Quan; Minglong Lei; Lingfeng Niu (Neural Networks, 2022)

Graph regularized locally linear embedding for unsupervised feature selection. - Jianyu Miao; Tiejun Yang; Lijun Sun; Xuan Fei; Lingfeng Niu; Yong Shi 001 (Pattern Recognit., 2022)

Sparse CapsNet with explicit regularizer. - Ruiyang Shi; Lingfeng Niu; Ruizhi Zhou (Pattern Recognit., 2022)

DigGCN: Learning Compact Graph Convolutional Networks via Diffusion Aggregation. - Minglong Lei; Pei Quan; Rongrong Ma; Yong Shi 001; Lingfeng Niu (IEEE Trans. Cybern., 2022)

Knowledge Graph Embedding by Double Limit Scoring Loss. - Xiaofei Zhou; Lingfeng Niu; Qiannan Zhu; Xingquan Zhu 001; Ping Liu 001; Jianlong Tan; Li Guo 001 (IEEE Trans. Knowl. Data Eng., 2022)

A Unified Pre-training and Adaptation Framework for Combinatorial Optimization on Graphs. - Ruibin Zeng; Minglong Lei; Lingfeng Niu; Lan Cheng (CoRR, 2023)

Training Compact DNNs with ℓ1/2 Regularization. - Anda Tang; Lingfeng Niu; Jianyu Miao; Peng Zhang 001 (Pattern Recognit., 2023)

Diluted binary neural network. - Yuhan Lin; Lingfeng Niu; Yang Xiao 017; Ruizhi Zhou (Pattern Recognit., 2023)

Federated learning with ℓ1 regularization. - Yong Shi 001; Yuanying Zhang; Peng Zhang 001; Yang Xiao 017; Lingfeng Niu (Pattern Recognit. Lett., 2023)

Graph Influence Network. - Yong Shi 001; Pei Quan; Yang Xiao 017; Minglong Lei; Lingfeng Niu (IEEE Trans. Cybern., 2023)

Wasserstein distance regularized graph neural networks. - Yong Shi 001; Lei Zheng; Pei Quan; Lingfeng Niu (Inf. Sci., 2024)

Two-level adversarial attacks for graph neural networks. - Chengxi Song; Lingfeng Niu; Minglong Lei (Inf. Sci., 2024)

Sparse optimization guided pruning for neural networks. - Yong Shi 001; Anda Tang; Lingfeng Niu; Ruizhi Zhou (Neurocomputing, 2024)

Sparse loss-aware ternarization for neural networks. - Ruizhi Zhou; Lingfeng Niu; Dachuan Xu (Inf. Sci., 2025)

ExGAT: Context extended graph attention neural network. - Pei Quan; Lei Zheng; Wen Zhang 001; Yang Xiao 017; Lingfeng Niu; Yong Shi 001 (Neural Networks, 2025)

A universal network strategy for lightspeed computation of entropy-regularized optimal transport. - Yong Shi 001; Lei Zheng; Pei Quan; Yang Xiao 017; Lingfeng Niu (Neural Networks, 2025)