Fast CU Size Decisions for HEVC Intra Frame Coding Based on Support Vector Machines. - Deyuan Liu; Xingang Liu; Yayong Li (DASC/PiCom/DataCom/CyberSciTech, 2016)

Fast Online-Learning Parameters Decision Algorithm Based on Bayesian Decision Rule for 3D-HEVC. - Yayong Li; Xingang Liu; Tao Yu; Yongyong Mei; Peicheng Wang (iThings/GreenCom/CPSCom/SmartData, 2016)

A Fast Coding Unit Size Decision Algorithm for HEVC Intra Coding Based on Image Complexity. - Deyuan Liu; Xingang Liu; Yayong Li (iThings/GreenCom/CPSCom/SmartData, 2016)

An Efficient H.264/AVC to HEVC Transcoder for Real-Time Video Communication in Internet of Vehicles. - Xingang Liu; Yayong Li; Cheng Dai; Pan Li 001; Laurence T. Yang (IEEE Internet Things J., 2018)

Semi-supervised Adversarial Active Learning on Attributed Graphs. - Yayong Li; Jie Yin 001; Ling Chen 006 (CoRR, 2019)

An Adaptive CU Size Decision Algorithm for HEVC Intra Prediction Based on Complexity Classification Using Machine Learning. - Xingang Liu; Yayong Li; Deyuan Liu; Peicheng Wang; Laurence T. Yang (IEEE Trans. Circuits Syst. Video Technol., 2019)

Unified Robust Training for Graph Neural Networks Against Label Noise. - Yayong Li; Jie Yin 001; Ling Chen 006 (PAKDD (1), 2021)

Wide Graph Neural Networks: Aggregation Provably Leads to Exponentially Trainability Loss. - Wei Huang 034; Yayong Li; Weitao Du; Richard Yi Da Xu; Jie Yin 001; Ling Chen 006 (CoRR, 2021)

Unified Robust Training for Graph NeuralNetworks against Label Noise. - Yayong Li; Jie Yin 001; Ling Chen 006 (CoRR, 2021)

SEAL: Semisupervised Adversarial Active Learning on Attributed Graphs. - Yayong Li; Jie Yin 001; Ling Chen 006 (IEEE Trans. Neural Networks Learn. Syst., 2021)

Attentive Feature Fusion for Credit Default Prediction. - Ximing Liu; Yayong Li; Cuiqing Jiang; Zhao Wang 010; Fuqing Zhao; Jianfei Wang (CSCWD, 2022)

Towards Deepening Graph Neural Networks: A GNTK-based Optimization Perspective. - Wei Huang 034; Yayong Li; Weitao Du; Richard Y. D. Xu; Jie Yin 001; Ling Chen 006; Miao Zhang (ICLR, 2022)

Informative pseudo-labeling for graph neural networks with few labels. - Yayong Li; Jie Yin 001; Ling Chen 006 (Data Min. Knowl. Discov., 2023)

Graph Condensation for Open-World Graph Learning. - Xinyi Gao 001; Tong Chen 005; Wentao Zhang 001; Yayong Li; Xiangguo Sun; Hongzhi Yin (KDD, 2024)

Contrastive Graph Condensation: Advancing Data Versatility through Self-Supervised Learning. - Xinyi Gao 001; Yayong Li; Tong Chen 005; Guanhua Ye; Wentao Zhang 001; Hongzhi Yin (CoRR, 2024)

A hierarchical attention-based feature selection and fusion method for credit risk assessment. - Ximing Liu; Yayong Li; Cheng Dai; Hong Zhang (Future Gener. Comput. Syst., 2024)

Inductive Graph Few-shot Class Incremental Learning. - Yayong Li; Peyman Moghadam; Can Peng; Nan Ye; Piotr Koniusz (WSDM, 2025)