default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDLingfeng Niu
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2025
[j43]Ruizhi Zhou, Lingfeng Niu
, Dachuan Xu:
Sparse loss-aware ternarization for neural networks. Inf. Sci. 693: 121668 (2025)- [j42]Pei Quan, Lei Zheng, Wen Zhang, Yang Xiao, Lingfeng Niu, Yong Shi:
ExGAT: Context extended graph attention neural network. Neural Networks 181: 106784 (2025) - [j41]Yong Shi, Lei Zheng, Pei Quan, Yang Xiao, Lingfeng Niu:
A universal network strategy for lightspeed computation of entropy-regularized optimal transport. Neural Networks 184: 107038 (2025) - 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, Junwei 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
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2025-01-21 00:04 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
