Ying Guo

According to our database, Ying Guo authored at least 20 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Consistency-Heterogenity Balanced Fake News Detection via Cross-Modal Matching.

Ying Guo, Bingxin Li, Kexin Zhen, Jie Liu, Gaolei Li, Qi Wang, Yong-Jin Liu

IEEE Trans. Artif. Intell., July, 2025

HCT: image super-resolution restoration using hierarchical convolution transformer networks.

Ying Guo, Chang Tian, Han Wang, Jie Liu, Chong Di, Keqing Ning

Pattern Anal. Appl., June, 2025

Dmvae: a dual-stream multi-modal variational autoencoder for multi-task fake news detection.

Ying Guo, Shuting Hu, Yao Li, Chong Di, Jie Liu

Pattern Anal. Appl., June, 2025

HADT: Image super-resolution restoration using Hybrid Attention-Dense Connected Transformer Networks.

Ying Guo, Chang Tian, Jie Liu, Chong Di, Keqing Ning

Neurocomputing, 2025

2024

Crowdsourcing Malware Family Annotation: Joint Class-Determined Tag Extraction and Weakly-Tagged Sample Inference.

Yongkang Jiang, Gaolei Li, Shenghong Li, Ying Guo, Kai Zhou

IEEE Trans. Netw. Serv. Manag., August, 2024

BenchMFC: A benchmark dataset for trustworthy malware family classification under concept drift.

Yongkang Jiang, Gaolei Li, Shenghong Li, Ying Guo

Comput. Secur., 2024

2023

Learning automata-accelerated greedy algorithms for stochastic submodular maximization.

Chong Di, Fangqi Li, Pengyao Xu, Ying Guo, Chao Chen, Minglei Shu

Knowl. Based Syst., December, 2023

An Auxiliary Modality Based Text-Image Matching Methodology for Fake News Detection.

Ying Guo, Bingxin Li, Hong Ge, Chong Di

Proceedings of the Artificial Neural Networks and Machine Learning, 2023

2022

A multi-Markovian switching-based strategy for solving the stochastic point location problem.

Ying Guo, Shenghong Li

Neural Comput. Appl., 2022

A novel reduced parameter s-model of estimator learning automata in the switching non-stationary environment.

Ying Guo, Chong Di, Shenghong Li

Neural Comput. Appl., 2022

2020

Learning Automata Based Competition Scheme to Train Deep Neural Networks.

Haonan Guo, Shenghong Li, Kaiyue Qi, Ying Guo, Zhengwu Xu

IEEE Trans. Emerg. Top. Comput. Intell., 2020

2019

A Non-Monte-Carlo Parameter-Free Learning Automata Scheme Based on Two Categories of Statistics.

Ying Guo, Shenghong Li

IEEE Trans. Cybern., 2019

Learning Automata-Based Access Class Barring Scheme for Massive Random Access in Machine-to-Machine Communications.

Chong Di, Bo Zhang, Qilian Liang, Shenghong Li, Ying Guo

IEEE Internet Things J., 2019

2017

Learning automata-based algorithms for solving the stochastic shortest path routing problems in 5G wireless communication.

Ying Guo, Shenghong Li, Wen Jiang, Bo Zhang, Yinghua Ma

Phys. Commun., 2017

A loss function based parameterless learning automaton scheme.

Ying Guo, Hao Ge, Shenghong Li

Neurocomputing, 2017

A set of novel continuous action-set reinforcement learning automata models to optimize continuous functions.

Ying Guo, Hao Ge, Shenghong Li

Appl. Intell., 2017

2016

A cooperative framework of learning automata and its application in tutorial-like system.

Hao Ge, Yifan Wang, Shenghong Li, Chun-Lung Philip Chen, Ying Guo

Neurocomputing, 2016

Gaussian Iteration: A Novel Way to Collaborative Filtering.

Xiaochun Li, Fangqi Li, Ying Guo, Jinchao Huang

Proceedings of the Intelligent Computing Methodologies - 12th International Conference, 2016

A New Scheme Based on HSSL for Solving the Stochastic Point Location Problem.

Jinchao Huang, Yan Yan, Ying Guo, Shenghong Li

Proceedings of the IEEE First International Conference on Data Science in Cyberspace, 2016

A General Strategy for Solving the Stochastic Point Location Problem by Utilizing the Correlation of Three Adjacent Nodes.

Ying Guo, Hao Ge, Jinchao Huang, Shenghong Li

Proceedings of the IEEE First International Conference on Data Science in Cyberspace, 2016