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Lingfeng Niu
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2020 – today
- 2024
- [j40]Yong Shi, Anda Tang, Lingfeng Niu, Ruizhi Zhou:
Sparse optimization guided pruning for neural networks. Neurocomputing 574: 127280 (2024) - [j39]Chengxi Song, Lingfeng Niu
, Minglong Lei
:
Two-level adversarial attacks for graph neural networks. Inf. Sci. 654: 119877 (2024) - [j38]Yong Shi, Lei Zheng
, Pei Quan
, Lingfeng Niu
:
Wasserstein distance regularized graph neural networks. Inf. Sci. 670: 120608 (2024) - 2023
- [j37]Anda Tang, Lingfeng Niu, Jianyu Miao, Peng Zhang:
Training Compact DNNs with ℓ1/2 Regularization. Pattern Recognit. 136: 109206 (2023) - [j36]Yuhan Lin, Lingfeng Niu, Yang Xiao, Ruizhi Zhou:
Diluted binary neural network. Pattern Recognit. 140: 109556 (2023) - [j35]Yong Shi, Yuanying Zhang, Peng Zhang
, Yang Xiao
, Lingfeng Niu
:
Federated learning with ℓ1 regularization. Pattern Recognit. Lett. 172: 15-21 (2023) - [j34]Yong Shi
, Pei Quan
, Yang Xiao
, Minglong Lei
, Lingfeng Niu
:
Graph Influence Network. IEEE Trans. Cybern. 53(10): 6146-6159 (2023) - [i6]Ruibin Zeng, Minglong Lei, Lingfeng Niu, Lan Cheng:
A Unified Pre-training and Adaptation Framework for Combinatorial Optimization on Graphs. CoRR abs/2312.11547 (2023) - 2022
- [j33]Jianyu Miao, Tiejun Yang, Jun-Wei Jin, Lijun Sun, Lingfeng Niu, Yong Shi:
Towards Compact Broad Learning System by Combined Sparse Regularization. Int. J. Inf. Technol. Decis. Mak. 21(1): 169-194 (2022) - [j32]Yang Xiao
, Pei Quan
, Minglong Lei
, Lingfeng Niu
:
Latent neighborhood-based heterogeneous graph representation. Neural Networks 154: 413-424 (2022) - [j31]Jianyu Miao, Tiejun Yang, Lijun Sun, Xuan Fei, Lingfeng Niu, Yong Shi:
Graph regularized locally linear embedding for unsupervised feature selection. Pattern Recognit. 122: 108299 (2022) - [j30]Ruiyang Shi
, Lingfeng Niu, Ruizhi Zhou:
Sparse CapsNet with explicit regularizer. Pattern Recognit. 124: 108486 (2022) - [j29]Minglong Lei
, Pei Quan
, Rongrong Ma, Yong Shi
, Lingfeng Niu
:
DigGCN: Learning Compact Graph Convolutional Networks via Diffusion Aggregation. IEEE Trans. Cybern. 52(2): 912-924 (2022) - [j28]Xiaofei Zhou
, Lingfeng Niu
, Qiannan Zhu
, Xingquan Zhu
, Ping Liu, Jianlong Tan, Li Guo:
Knowledge Graph Embedding by Double Limit Scoring Loss. IEEE Trans. Knowl. Data Eng. 34(12): 5825-5839 (2022) - [c39]Anda Tang, Tongsheng Yao, Lingfeng Niu, Yong Shi:
Sparse Learning for Neural Networks with A Generalized Sparse Regularization. ITQM 2022: 747-754 - [c38]Lei Zheng, Pei Quan, Minglong Lei, Yang Xiao
, Lingfeng Niu:
Optimal Transport Guided Node Classification in Cross Networks. ITQM 2022: 1160-1167 - [c37]Yong Shi, Yuanying Zhang, Yang Xiao, Lingfeng Niu:
Optimization Strategies for Client Drift in Federated Learning: A review. ITQM 2022: 1168-1173 - 2021
- [j27]Ruizhi Zhou, Lingfeng Niu, Hong Yang:
Unsupervised feature selection for attributed graphs. Expert Syst. Appl. 168: 114402 (2021) - [j26]Jianyu Miao, Yuan Ping
, Zhensong Chen, Xiao-Bo Jin, Peijia Li, Lingfeng Niu:
Unsupervised feature selection by non-convex regularized self-representation. Expert Syst. Appl. 173: 114643 (2021) - [j25]Ruizhi Zhou, Qin Zhang, Peng Zhang, Lingfeng Niu
, Xiaodong Lin
:
Anomaly detection in dynamic attributed networks. Neural Comput. Appl. 33(6): 2125-2136 (2021) - [j24]Yong Shi, Yang Xiao
, Pei Quan
, Minglong Lei
, Lingfeng Niu
:
Distant Supervision Relation Extraction via adaptive dependency-path and additional knowledge graph supervision. Neural Networks 134: 42-53 (2021) - [j23]Yong Shi, Yang Xiao
, Pei Quan
, Minglong Lei, Lingfeng Niu:
Document-level relation extraction via graph transformer networks and temporal convolutional networks. Pattern Recognit. Lett. 149: 150-156 (2021) - [c36]Lei Zheng, Yang Xiao
, Lingfeng Niu:
A brief survey on Computational Gromov-Wasserstein distance. ITQM 2021: 697-702 - [c35]Anda Tang, Pei Quan
, Lingfeng Niu, Yong Shi:
A survey of sparse regularization based compression methods. ITQM 2021: 703-709 - [i5]Minglong Lei, Yong Shi, Lingfeng Niu:
Latent Network Embedding via Adversarial Auto-encoders. CoRR abs/2109.15257 (2021) - [i4]Yating Ren, Junzhong Ji, Lingfeng Niu, Minglong Lei:
Multi-task Self-distillation for Graph-based Semi-Supervised Learning. CoRR abs/2112.01174 (2021) - 2020
- [j22]Ruizhi Zhou, Lingfeng Niu
:
Feature Selection of Network Data VIA ℓ2, p Regularization. Cogn. Comput. 12(6): 1217-1232 (2020) - [c34]Hong Yang, Ling Chen, Minglong Lei, Lingfeng Niu, Chuan Zhou, Peng Zhang:
Discrete Embedding for Latent Networks. IJCAI 2020: 1223-1229 - [c33]Shichao Guo, Yang Xiao
, Lingfeng Niu:
GGTAN: Graph Gated Talking-Heads Attention Networks for Traveling Salesman Problem. WI/IAT 2020: 676-681 - [c32]Ruiyang Shi
, Lingfeng Niu:
A brief survey on Capsule Network. WI/IAT 2020: 682-686
2010 – 2019
- 2019
- [j21]Yong Shi, Minglong Lei, Rongrong Ma, Lingfeng Niu
:
Learning Robust Auto-Encoders With Regularizer for Linearity and Sparsity. IEEE Access 7: 17195-17206 (2019) - [j20]Jianyu Miao
, Tiejun Yang
, Jun-Wei Jin
, Lingfeng Niu
:
Graph-Based Clustering via Group Sparsity and Manifold Regularization. IEEE Access 7: 172123-172135 (2019) - [j19]Jianyu Miao, Heling Cao, Xiao-Bo Jin, Rongrong Ma, Xuan Fei, Lingfeng Niu:
Joint Sparse Regularization for Dictionary Learning. Cogn. Comput. 11(5): 697-710 (2019) - [j18]Yong Shi, Peijia Li, Hao Yuan, Jianyu Miao, Lingfeng Niu:
Fast kernel extreme learning machine for ordinal regression. Knowl. Based Syst. 177: 44-54 (2019) - [j17]Yong Shi, Jianyu Miao, Lingfeng Niu
:
Feature selection with MCP $$^2$$ 2 regularization. Neural Comput. Appl. 31(10): 6699-6709 (2019) - [j16]Rongrong Ma, Jianyu Miao, Lingfeng Niu, Peng Zhang:
Transformed ℓ1 regularization for learning sparse deep neural networks. Neural Networks 119: 286-298 (2019) - [j15]Yong Shi
, Minglong Lei
, Hong Yang, Lingfeng Niu
:
Diffusion network embedding. Pattern Recognit. 88: 518-531 (2019) - [c31]Yong Shi, Yang Xiao
, Lingfeng Niu:
A Brief Survey of Relation Extraction Based on Distant Supervision. ICCS (3) 2019: 293-303 - [c30]Yuhan Lin, Minglong Lei, Lingfeng Niu:
Optimization Strategies in Quantized Neural Networks: A Review. ICDM Workshops 2019: 385-390 - [c29]Anda Tang, Rongrong Ma, Jianyu Miao, Lingfeng Niu:
Sparse Optimization Based on Non-convex ℓ 1/2 Regularization for Deep Neural Networks. ICDS 2019: 158-166 - [c28]Pei Quan
, Yong Shi, Minglong Lei, Jiaxu Leng, Tianlin Zhang
, Lingfeng Niu:
A Brief Review of Receptive Fields in Graph Convolutional Networks. WI (Companion) 2019: 106-110 - [i3]Rongrong Ma, Jianyu Miao, Lingfeng Niu, Peng Zhang:
Transformed 𝓁1 Regularization for Learning Sparse Deep Neural Networks. CoRR abs/1901.01021 (2019) - 2018
- [j14]Ruizhi Zhou, Xin Shen, Lingfeng Niu
:
A fast algorithm for nonsmooth penalized clustering. Neurocomputing 273: 583-592 (2018) - [j13]Fan Meng, Zhiquan Qi, Yingjie Tian
, Lingfeng Niu:
Pedestrian detection based on the privileged information. Neural Comput. Appl. 29(12): 1485-1494 (2018) - [j12]Zhiquan Qi
, Fan Meng, Yingjie Tian
, Lingfeng Niu
, Yong Shi
, Peng Zhang:
Adaboost-LLP: A Boosting Method for Learning With Label Proportions. IEEE Trans. Neural Networks Learn. Syst. 29(8): 3548-3559 (2018) - [j11]Yong Shi
, Jianyu Miao, Zhengyu Wang
, Peng Zhang, Lingfeng Niu
:
Feature Selection With ℓ2, 1-2 Regularization. IEEE Trans. Neural Networks Learn. Syst. 29(10): 4967-4982 (2018) - [c27]Hao Yuan, Bo Wang, Lingfeng Niu:
Kernel Extreme Learning Machine for Learning from Label Proportions. ICCS (2) 2018: 400-409 - [c26]Minglong Lei, Yong Shi, Peijia Li, Lingfeng Niu:
Deep Streaming Graph Representations. ICCS (3) 2018: 512-518 - [c25]Rongrong Ma, Lingfeng Niu:
Compact Deep Neural Networks with ℓ1, 1 and ℓ1, 2 Regularization. ICDM Workshops 2018: 1248-1254 - [c24]Pei Quan
, Yong Shi, Lingfeng Niu, Ying Liu, Tianlin Zhang:
Automatic Chinese Multiple-Choice Question Generation for Human Resource Performance Appraisal. ITQM 2018: 165-172 - [c23]Minglong Lei, Yong Shi, Lingfeng Niu:
The Applications of Stochastic Models in Network Embedding: A Survey. WI 2018: 635-638 - [c22]Rongrong Ma, Lingfeng Niu:
A Survey of Sparse-Learning Methods for Deep Neural Networks. WI 2018: 647-650 - [i2]Yong Shi, Minglong Lei, Peng Zhang, Lingfeng Niu:
Diffusion Based Network Embedding. CoRR abs/1805.03504 (2018) - [i1]Yong Shi, Huadong Wang, Xin Shen, Lingfeng Niu:
A Novel Large-scale Ordinal Regression Model. CoRR abs/1812.08237 (2018) - 2017
- [j10]Xin Shen, Lingfeng Niu, Zhiquan Qi, Yingjie Tian
:
Support vector machine classifier with truncated pinball loss. Pattern Recognit. 68: 199-210 (2017) - [j9]Lingfeng Niu, Ruizhi Zhou, Yingjie Tian
, Zhiquan Qi, Peng Zhang:
Nonsmooth Penalized Clustering via ℓp Regularized Sparse Regression. IEEE Trans. Cybern. 47(6): 1423-1433 (2017) - [j8]Zhiquan Qi, Bo Wang, Fan Meng, Lingfeng Niu
:
Learning With Label Proportions via NPSVM. IEEE Trans. Cybern. 47(10): 3293-3305 (2017) - [j7]Huadong Wang, Yong Shi, Lingfeng Niu
, Yingjie Tian
:
Nonparallel Support Vector Ordinal Regression. IEEE Trans. Cybern. 47(10): 3306-3317 (2017) - [c21]Huadong Wang, Jianyu Miao, Seyed Mojtaba Hosseini Bamakan
, Lingfeng Niu, Yong Shi:
Large-scale Nonparallel Support Vector Ordinal Regression Solver. ICCS 2017: 1261-1270 - [c20]Jianyu Miao, Yong Shi, Lingfeng Niu:
A Feasible Direction Method for Optimization Problem with Orthogonal Constraint in Feature Selection. ICDM Workshops 2017: 824-829 - [c19]Yong Shi, Peijia Li, Lingfeng Niu:
Augmented SVM with ordinal partitioning for text classification. WI 2017: 959-962 - 2016
- [c18]Jianyu Miao, Yong Shi, Lingfeng Niu:
Robust Unsupervised Feature Learning from Time-Series. WI Workshops 2016: 37-40 - 2015
- [j6]Xi Zhao, Yong Shi, Lingfeng Niu:
Kernel based simple regularized multiple criteria linear program for binary classification and regression. Intell. Data Anal. 19(3): 505-527 (2015) - [j5]Zhiquan Qi, Yingjie Tian
, Lingfeng Niu, Bo Wang:
Semi-supervised classification with privileged information. Int. J. Mach. Learn. Cybern. 6(4): 667-676 (2015) - [c17]Xin Shen, Lingfeng Niu, Yingjie Tian
, Yong Shi:
Alternating Direction Method of Multipliers for Nonparallel Support Vector Machines. ICDM Workshops 2015: 1171-1176 - [c16]Yong Shi, Huadong Wang, Lingfeng Niu:
Large-Scale Linear Support Vector Ordinal Regression Solver. ICDM Workshops 2015: 1177-1184 - [c15]Zhiquan Qi, Yingjie Tian
, Lingfeng Niu, Fan Meng, Limeng Cui, Yong Shi:
Pedestrian Detection Using Privileged Information. ICDM Workshops 2015: 1185-1188 - [c14]Ruizhi Zhou, Lingfeng Niu, Zhiquan Qi:
Smoothing Trust Region for Digital Image Restoration. WI-IAT (3) 2015: 40-43 - 2014
- [c13]Lingfeng Niu, Xi Zhao, Yong Shi:
A First-Order Decomposition Algorithm for Training Bound-Constrained Support Vector Machines. WI-IAT (1) 2014: 436-441 - 2013
- [j4]Xiaojun Chen
, Lingfeng Niu, Yaxiang Yuan:
Optimality Conditions and a Smoothing Trust Region Newton Method for NonLipschitz Optimization. SIAM J. Optim. 23(3): 1528-1552 (2013) - [c12]Xi Zhao, Lingfeng Niu, Yong Shi:
Kernel Based Simple Regularized Multiple Criteria Linear Programs for Binary Classification. Web Intelligence/IAT Workshops 2013: 58-61 - [c11]Lingfeng Niu, Xi Zhao, Yong Shi:
A Simple Regularized Multiple Criteria Linear Programs for Binary Classification. ICCS 2013: 1690-1699 - [c10]Lingfeng Niu, Xi Zhao:
A Simple Decomposition Alternating Direction Method for Matrix Completion. ITQM 2013: 149-157 - 2012
- [j3]Lingfeng Niu, Jianmin Wu, Yong Shi:
Training the max-margin sequence model with the relaxed slack variables. Neural Networks 33: 228-235 (2012) - [c9]Lingfeng Niu, Yong Shi, Jianmin Wu:
Learning Using Privileged Information with L-1 Support Vector Machine. Web Intelligence/IAT Workshops 2012: 10-14 - [c8]Lingfeng Niu, Jianmin Wu:
Nonlinear L-1 Support Vector Machines for Learning Using Privileged Information. ICDM Workshops 2012: 495-499 - [c7]Lingfeng Niu, Jianmin Wu, Yong Shi:
Entity Disambiguation with Textual and Connection Information. ICCS 2012: 1249-1255 - 2011
- [j2]Lingfeng Niu:
Parallel algorithm for training multiclass proximal Support Vector Machines. Appl. Math. Comput. 217(12): 5328-5337 (2011) - [j1]Lingfeng Niu, Yaxiang Yuan:
A parallel decomposition algorithm for training multiclass kernel-based vector machines. Optim. Methods Softw. 26(3): 431-454 (2011) - [c6]Lingfeng Niu, Yong Shi:
MSSVM: A Modular Solver for Support Vector Machines. Web Intelligence/IAT Workshops 2011: 225-228 - [c5]Lingfeng Niu, Jianmin Wu, Yong Shi:
Entity Resolution with Attribute and Connection Graph. ICDM Workshops 2011: 267-271 - [c4]Lingfeng Niu, Jianmin Wu, Yong Shi:
Second-order Mining for Active Collaborative Filtering. ICCS 2011: 1726-1734 - 2010
- [c3]Lingfeng Niu, Yong Shi:
Using Projection Gradient Method to Train Linear Support Vector Machines. Web Intelligence/IAT Workshops 2010: 207-210 - [c2]Lingfeng Niu, Yong Shi:
Semi-supervised PLSA for Document Clustering. ICDM Workshops 2010: 1196-1203 - [c1]Lingfeng Niu, Yong Shi:
A new training method for sequence data. ICCS 2010: 2391-2396
Coauthor Index
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last updated on 2024-06-03 00:11 CEST by the dblp team
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