Lingfeng Niu

Orcid: 0000-0002-5827-8449

According to our database1, Lingfeng Niu authored at least 85 papers between 2010 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Sparse optimization guided pruning for neural networks.
Neurocomputing, March, 2024

Two-level adversarial attacks for graph neural networks.
Inf. Sci., January, 2024

Wasserstein distance regularized graph neural networks.
Inf. Sci., 2024

2023
Graph Influence Network.
IEEE Trans. Cybern., October, 2023

Federated learning with ℓ1 regularization.
Pattern Recognit. Lett., August, 2023

Diluted binary neural network.
Pattern Recognit., August, 2023

Training Compact DNNs with ℓ1/2 Regularization.
Pattern Recognit., April, 2023

A Unified Pre-training and Adaptation Framework for Combinatorial Optimization on Graphs.
CoRR, 2023

2022
Knowledge Graph Embedding by Double Limit Scoring Loss.
IEEE Trans. Knowl. Data Eng., 2022

DigGCN: Learning Compact Graph Convolutional Networks via Diffusion Aggregation.
IEEE Trans. Cybern., 2022

Sparse CapsNet with explicit regularizer.
Pattern Recognit., 2022

Graph regularized locally linear embedding for unsupervised feature selection.
Pattern Recognit., 2022

Latent neighborhood-based heterogeneous graph representation.
Neural Networks, 2022

Towards Compact Broad Learning System by Combined Sparse Regularization.
Int. J. Inf. Technol. Decis. Mak., 2022

Optimal Transport Guided Node Classification in Cross Networks.
Proceedings of the 9th International Conference on Information Technology and Quantitative Management, 2022

Sparse Learning for Neural Networks with A Generalized Sparse Regularization.
Proceedings of the 9th International Conference on Information Technology and Quantitative Management, 2022

Optimization Strategies for Client Drift in Federated Learning: A review.
Proceedings of the 9th International Conference on Information Technology and Quantitative Management, 2022

2021
Document-level relation extraction via graph transformer networks and temporal convolutional networks.
Pattern Recognit. Lett., 2021

Distant Supervision Relation Extraction via adaptive dependency-path and additional knowledge graph supervision.
Neural Networks, 2021

Anomaly detection in dynamic attributed networks.
Neural Comput. Appl., 2021

Unsupervised feature selection for attributed graphs.
Expert Syst. Appl., 2021

Unsupervised feature selection by non-convex regularized self-representation.
Expert Syst. Appl., 2021

Multi-task Self-distillation for Graph-based Semi-Supervised Learning.
CoRR, 2021

Latent Network Embedding via Adversarial Auto-encoders.
CoRR, 2021

A brief survey on Computational Gromov-Wasserstein distance.
Proceedings of the 8th International Conference on Information Technology and Quantitative Management, 2021

A survey of sparse regularization based compression methods.
Proceedings of the 8th International Conference on Information Technology and Quantitative Management, 2021

2020
Feature Selection of Network Data VIA ℓ<sub>2, p</sub> Regularization.
Cogn. Comput., 2020

A brief survey on Capsule Network.
Proceedings of the IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, 2020

GGTAN: Graph Gated Talking-Heads Attention Networks for Traveling Salesman Problem.
Proceedings of the IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, 2020

Discrete Embedding for Latent Networks.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019
Diffusion network embedding.
Pattern Recognit., 2019

Transformed ℓ1 regularization for learning sparse deep neural networks.
Neural Networks, 2019

Feature selection with MCP $$^2$$ 2 regularization.
Neural Comput. Appl., 2019

Fast kernel extreme learning machine for ordinal regression.
Knowl. Based Syst., 2019

Transformed 𝓁<sub>1</sub> Regularization for Learning Sparse Deep Neural Networks.
CoRR, 2019

Joint Sparse Regularization for Dictionary Learning.
Cogn. Comput., 2019

Learning Robust Auto-Encoders With Regularizer for Linearity and Sparsity.
IEEE Access, 2019

Graph-Based Clustering via Group Sparsity and Manifold Regularization.
IEEE Access, 2019

A Brief Review of Receptive Fields in Graph Convolutional Networks.
Proceedings of the 2019 IEEE/WIC/ACM International Conference on Web Intelligence, 2019

Sparse Optimization Based on Non-convex ℓ <sub>1/2</sub> Regularization for Deep Neural Networks.
Proceedings of the Data Science - 6th International Conference, 2019

Optimization Strategies in Quantized Neural Networks: A Review.
Proceedings of the 2019 International Conference on Data Mining Workshops, 2019

A Brief Survey of Relation Extraction Based on Distant Supervision.
Proceedings of the Computational Science - ICCS 2019, 2019

2018
Feature Selection With ℓ<sub>2, 1-2</sub> Regularization.
IEEE Trans. Neural Networks Learn. Syst., 2018

Adaboost-LLP: A Boosting Method for Learning With Label Proportions.
IEEE Trans. Neural Networks Learn. Syst., 2018

Pedestrian detection based on the privileged information.
Neural Comput. Appl., 2018

A fast algorithm for nonsmooth penalized clustering.
Neurocomputing, 2018

A Novel Large-scale Ordinal Regression Model.
CoRR, 2018

Diffusion Based Network Embedding.
CoRR, 2018

A Survey of Sparse-Learning Methods for Deep Neural Networks.
Proceedings of the 2018 IEEE/WIC/ACM International Conference on Web Intelligence, 2018

The Applications of Stochastic Models in Network Embedding: A Survey.
Proceedings of the 2018 IEEE/WIC/ACM International Conference on Web Intelligence, 2018

Automatic Chinese Multiple-Choice Question Generation for Human Resource Performance Appraisal.
Proceedings of the 6th International Conference on Information Technology and Quantitative Management, 2018

Compact Deep Neural Networks with ℓ1, 1 and ℓ1, 2 Regularization.
Proceedings of the 2018 IEEE International Conference on Data Mining Workshops, 2018

Kernel Extreme Learning Machine for Learning from Label Proportions.
Proceedings of the Computational Science - ICCS 2018, 2018

Deep Streaming Graph Representations.
Proceedings of the Computational Science - ICCS 2018, 2018

2017
Nonparallel Support Vector Ordinal Regression.
IEEE Trans. Cybern., 2017

Learning With Label Proportions via NPSVM.
IEEE Trans. Cybern., 2017

Nonsmooth Penalized Clustering via ℓ<sub>p</sub> Regularized Sparse Regression.
IEEE Trans. Cybern., 2017

Support vector machine classifier with truncated pinball loss.
Pattern Recognit., 2017

Augmented SVM with ordinal partitioning for text classification.
Proceedings of the International Conference on Web Intelligence, 2017

A Feasible Direction Method for Optimization Problem with Orthogonal Constraint in Feature Selection.
Proceedings of the 2017 IEEE International Conference on Data Mining Workshops, 2017

Large-scale Nonparallel Support Vector Ordinal Regression Solver.
Proceedings of the International Conference on Computational Science, 2017

2016
Robust Unsupervised Feature Learning from Time-Series.
Proceedings of the 2016 IEEE/WIC/ACM International Conference on Web Intelligence, 2016

2015
Semi-supervised classification with privileged information.
Int. J. Mach. Learn. Cybern., 2015

Kernel based simple regularized multiple criteria linear program for binary classification and regression.
Intell. Data Anal., 2015

Smoothing Trust Region for Digital Image Restoration.
Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, 2015

Large-Scale Linear Support Vector Ordinal Regression Solver.
Proceedings of the IEEE International Conference on Data Mining Workshop, 2015

Alternating Direction Method of Multipliers for Nonparallel Support Vector Machines.
Proceedings of the IEEE International Conference on Data Mining Workshop, 2015

Pedestrian Detection Using Privileged Information.
Proceedings of the IEEE International Conference on Data Mining Workshop, 2015

2014
A First-Order Decomposition Algorithm for Training Bound-Constrained Support Vector Machines.
Proceedings of the 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), Warsaw, Poland, August 11-14, 2014, 2014

2013
Optimality Conditions and a Smoothing Trust Region Newton Method for NonLipschitz Optimization.
SIAM J. Optim., 2013

A Simple Decomposition Alternating Direction Method for Matrix Completion.
Proceedings of the First International Conference on Information Technology and Quantitative Management, 2013

A Simple Regularized Multiple Criteria Linear Programs for Binary Classification.
Proceedings of the International Conference on Computational Science, 2013

Kernel Based Simple Regularized Multiple Criteria Linear Programs for Binary Classification.
Proceedings of the 2013 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, 2013

2012
Entity Disambiguation with Textual and Connection Information.
Proceedings of the International Conference on Computational Science, 2012

Training the max-margin sequence model with the relaxed slack variables.
Neural Networks, 2012

Nonlinear L-1 Support Vector Machines for Learning Using Privileged Information.
Proceedings of the 12th IEEE International Conference on Data Mining Workshops, 2012

Learning Using Privileged Information with L-1 Support Vector Machine.
Proceedings of the 2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, 2012

2011
Second-order Mining for Active Collaborative Filtering.
Proceedings of the International Conference on Computational Science, 2011

A parallel decomposition algorithm for training multiclass kernel-based vector machines.
Optim. Methods Softw., 2011

Parallel algorithm for training multiclass proximal Support Vector Machines.
Appl. Math. Comput., 2011

Entity Resolution with Attribute and Connection Graph.
Proceedings of the Data Mining Workshops (ICDMW), 2011

MSSVM: A Modular Solver for Support Vector Machines.
Proceedings of the 2011 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, 2011

2010
A new training method for sequence data.
Proceedings of the International Conference on Computational Science, 2010

Semi-supervised PLSA for Document Clustering.
Proceedings of the ICDMW 2010, 2010

Using Projection Gradient Method to Train Linear Support Vector Machines.
Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and International Conference on Intelligent Agent Technology - Workshops, Toronto, Canada, August 31, 2010


  Loading...