An Improved News Recommendation Algorithm Based on Text Similarity. - Yihang Gao; Hui Zhao 002; Qian Zhou; Meikang Qiu; Meiqin Liu 001 (SmartBlock, 2020)

Research on Sentiment Dictionary Based on Sentiment Analysis in News Domain. - Yihang Gao; Peng Su; Hui Zhao 002; Meikang Qiu; Meiqin Liu 001 (BigDataSecurity, 2021)

Approximation for Probability Distributions by Wasserstein GAN. - Yihang Gao; Michael K. Ng 001 (CoRR, 2021)

Approximate Secular Equations for the Cubic Regularization Subproblem. - Yihang Gao; Man-Chung Yue; Michael Ng 001 (NeurIPS, 2022)

SVD-PINNs: Transfer Learning of Physics-Informed Neural Networks via Singular Value Decomposition. - Yihang Gao; Ka Chun Cheung; Michael K. Ng 001 (SSCI, 2022)

HessianFR: An Efficient Hessian-based Follow-the-Ridge Algorithm for Minimax Optimization. - Yihang Gao; Huafeng Liu 001; Michael K. Ng 001; Mingjie Zhou (CoRR, 2022)

A Momentum Accelerated Adaptive Cubic Regularization Method for Nonconvex Optimization. - Yihang Gao; Michael Kwok-Po Ng (CoRR, 2022)

Wasserstein generative adversarial uncertainty quantification in physics-informed neural networks. - Yihang Gao; Michael K. Ng 001 (J. Comput. Phys., 2022)

Gradient Descent Finds the Global Optima of Two-Layer Physics-Informed Neural Networks. - Yihang Gao; Yiqi Gu; Michael Ng 001 (ICML, 2023)

Approximating Probability Distributions by Using Wasserstein Generative Adversarial Networks. - Yihang Gao; Michael K. Ng 001; Mingjie Zhou (SIAM J. Math. Data Sci., 2023)

Super-resolved Estimation of White Matter Microstructure via 3D Conditional Latent Diffusion Model. - Jiquan Ma; Yihang Gao; Haotian Jiang; Jing Gu; Diliara Khairullina; Hui Cui 002; Geng Chen 001 (BIBM, 2024)

DAPE: Data-Adaptive Positional Encoding for Length Extrapolation. - Chuanyang Zheng; Yihang Gao; Han Shi; Minbin Huang; Jingyao Li; Jing Xiong; Xiaozhe Ren; Michael K. Ng 001; Xin Jiang; Zhenguo Li; Yu Li (NeurIPS, 2024)

On the Expressive Power of a Variant of the Looped Transformer. - Yihang Gao; Chuanyang Zheng; Enze Xie; Han Shi; Tianyang Hu; Yu Li; Michael K. Ng 001; Zhenguo Li; Zhaoqiang Liu (CoRR, 2024)

CAPE: Context-Adaptive Positional Encoding for Length Extrapolation. - Chuanyang Zheng; Yihang Gao; Han Shi; Minbin Huang; Jingyao Li; Jing Xiong; Xiaozhe Ren; Michael K. Ng 001; Xin Jiang; Zhenguo Li; Yu Li (CoRR, 2024)

SepLLM: Accelerate Large Language Models by Compressing One Segment into One Separator. - Guoxuan Chen; Han Shi; Jiawei Li; Yihang Gao; Xiaozhe Ren; Yimeng Chen; Xin Jiang; Zhenguo Li; Weiyang Liu; Chao Huang (CoRR, 2024)

DAPE V2: Process Attention Score as Feature Map for Length Extrapolation. - Chuanyang Zheng; Yihang Gao; Han Shi; Jing Xiong; Jiankai Sun; Jingyao Li; Minbin Huang; Xiaozhe Ren; Michael Ng 001; Xin Jiang; Zhenguo Li; Yu Li (ACL (1), 2025)

FastPAD: A fast self-supervised image anomaly detection method based on patch aggregation and discrimination. - Yihang Gao; Zhiyan Han; Jian Wang (Neurocomputing, 2025)

Neighborhood Topology-Aware Knowledge Graph Learning and Microbial Preference Inferring for Drug-Microbe Association Prediction. - Jing Gu; Tiangang Zhang; Yihang Gao; Sentao Chen; Yuxin Zhang; Hui Cui 002; Ping Xuan (J. Chem. Inf. Model., 2025)

AlgoFormer: An Efficient Transformer Framework with Algorithmic Structures. - Yihang Gao; Chuanyang Zheng; Enze Xie; Han Shi; Tianyang Hu; Yu Li; Michael Ng 001; Zhenguo Li; Zhaoqiang Liu (Trans. Mach. Learn. Res., 2025)

Low Tensor-Rank Adaptation of Kolmogorov-Arnold Networks. - Yihang Gao; Michael K. P. Ng 001; Vincent Y. F. Tan (IEEE Trans. Signal Process., 2025)

Self-Adjust Softmax. - Chuanyang Zheng; Yihang Gao; Guoxuan Chen; Han Shi; Jing Xiong; Xiaozhe Ren; Chao Huang; Xin Jiang; Zhenguo Li; Yu Li (CoRR, 2025)

Automatic Rank Determination for Low-Rank Adaptation via Submodular Function Maximization. - Yihang Gao; Vincent Y. F. Tan (CoRR, 2025)

SAS: Simulated Attention Score. - Chuanyang Zheng; Jiankai Sun; Yihang Gao; Yuehao Wang; Peihao Wang; Jing Xiong; Liliang Ren; Hao Cheng 002; Janardhan Kulkarni; Yelong Shen; Atlas Wang; Mac Schwager; et al. (CoRR, 2025)

On the Convergence of (Stochastic) Gradient Descent for Kolmogorov-Arnold Networks. - Yihang Gao; Vincent Y. F. Tan (IEEE Trans. Inf. Theory, 2025)