Yihang Gao

41 papers A* 5Journal 31Unranked 5
YearRankTypeTitle / Venue / Authors
2026 J jnl
Automatic Rank Determination for Low-Rank Adaptation via Submodular Function Maximization.
IEEE Trans. Signal Process.
Yihang Gao, Vincent Y. F. Tan
2026 J jnl
Consensus of multi-agent systems under variable denial-of-service attacks: Noise-based event-triggered protocols.
Appl. Math. Comput.
Sen Li, Yihang Gao, Wenxue Li
2026 J jnl
GeoNorm: Unify Pre-Norm and Post-Norm with Geodesic Optimization.
CoRR
Chuanyang Zheng, Jiankai Sun, Yihang Gao, Chi Wang, Yuehao Wang, Jing Xiong, Liliang Ren, Bo Peng, Qingmei Wang, Xiaoran Shang, Mac Schwager, Anderson Schneider, Yuriy Nevmyvaka, Xiaodong Liu
2026 J jnl
ODELoRA: Training Low-Rank Adaptation by Solving Ordinary Differential Equations.
CoRR
Yihang Gao, Vincent Y. F. Tan
2026 J jnl
Super-resolved microstructure estimation with 3D dual-conditioned latent diffusion model.
Knowl. Based Syst.
Jiquan Ma, Yu Guo, Yihang Gao, Fanhui Kong, Xiuchun Li, Hui Cui, Haotian Jiang, Geng Chen
2025 J jnl
AlgoFormer: An Efficient Transformer Framework with Algorithmic Structures.
Trans. Mach. Learn. Res.
Yihang Gao, Chuanyang Zheng, Enze Xie, Han Shi, Tianyang Hu, Yu Li, Michael Ng, Zhenguo Li, Zhaoqiang Liu
2025 J jnl
Automatic Rank Determination for Low-Rank Adaptation via Submodular Function Maximization.
CoRR
Yihang Gao, Vincent Y. F. Tan
2025 — conf
DAPE V2: Process Attention Score as Feature Map for Length Extrapolation.
ACL (1)
Chuanyang Zheng, Yihang Gao, Han Shi, Jing Xiong, Jiankai Sun, Jingyao Li, Minbin Huang, Xiaozhe Ren, Michael Ng, Xin Jiang, Zhenguo Li, Yu Li
2025 J jnl
FastPAD: A fast self-supervised image anomaly detection method based on patch aggregation and discrimination.
Neurocomputing
Yihang Gao, Zhiyan Han, Jian Wang
2025 J jnl
GenAR: Next-Scale Autoregressive Generation for Spatial Gene Expression Prediction.
CoRR
Jiarui Ouyang, Yihui Wang, Yihang Gao, Yingxue Xu, Shu Yang, Hao Chen
2025 J jnl
Low Tensor-Rank Adaptation of Kolmogorov-Arnold Networks.
CoRR
Yihang Gao, Michael K. Ng, Vincent Y. F. Tan
2025 J jnl
Low Tensor-Rank Adaptation of Kolmogorov-Arnold Networks.
IEEE Trans. Signal Process.
Yihang Gao, Michael K. P. Ng, Vincent Y. F. Tan
2025 J jnl
NLAFormer: Transformers Learn Numerical Linear Algebra Operations.
CoRR
Zhantao Ma, Yihang Gao, Michael K. Ng
2025 J jnl
Neighborhood Topology-Aware Knowledge Graph Learning and Microbial Preference Inferring for Drug-Microbe Association Prediction.
J. Chem. Inf. Model.
Jing Gu, Tiangang Zhang, Yihang Gao, Sentao Chen, Yuxin Zhang, Hui Cui, Ping Xuan
2025 J jnl
On the Convergence of (Stochastic) Gradient Descent for Kolmogorov-Arnold Networks.
IEEE Trans. Inf. Theory
Yihang Gao, Vincent Y. F. Tan
2025 J jnl
Online Inference of Constrained Optimization: Primal-Dual Optimality and Sequential Quadratic Programming.
CoRR
Yihang Gao, Michael K. Ng, Michael W. Mahoney, Sen Na
2025 J jnl
SAS: Simulated Attention Score.
CoRR
Chuanyang Zheng, Jiankai Sun, Yihang Gao, Yuehao Wang, Peihao Wang, Jing Xiong, Liliang Ren, Hao Cheng, Janardhan Kulkarni, Yelong Shen, Atlas Wang, Mac Schwager, Anderson Schneider, Xiaodong Liu, Jianfeng Gao
2025 A* conf
Self-Adjust Softmax.
EMNLP
Chuanyang Zheng, Yihang Gao, Guoxuan Chen, Han Shi, Jing Xiong, Xiaozhe Ren, Chao Huang, Zhenguo Li, Yu Li
2025 J jnl
Self-Adjust Softmax.
CoRR
Chuanyang Zheng, Yihang Gao, Guoxuan Chen, Han Shi, Jing Xiong, Xiaozhe Ren, Chao Huang, Xin Jiang, Zhenguo Li, Yu Li
2025 A* conf
SepLLM: Accelerate Large Language Models by Compressing One Segment into One Separator.
ICML
Guoxuan Chen, Han Shi, Jiawei Li, Yihang Gao, Xiaozhe Ren, Yimeng Chen, Xin Jiang, Zhenguo Li, Weiyang Liu, Chao Huang
2025 J jnl
Understanding the Mixture-of-Experts with Nadaraya-Watson Kernel.
CoRR
Chuanyang Zheng, Jiankai Sun, Yihang Gao, Enze Xie, Yuehao Wang, Peihao Wang, Ting Xu, Matthew Chang, Liliang Ren, Jingyao Li, Jing Xiong, Kashif Rasul, Mac Schwager, Anderson Schneider, Zhangyang Wang, Yuriy Nevmyvaka
2024 J jnl
CAPE: Context-Adaptive Positional Encoding for Length Extrapolation.
CoRR
Chuanyang Zheng, Yihang Gao, Han Shi, Minbin Huang, Jingyao Li, Jing Xiong, Xiaozhe Ren, Michael K. Ng, Xin Jiang, Zhenguo Li, Yu Li
2024 J jnl
DAPE V2: Process Attention Score as Feature Map for Length Extrapolation.
CoRR
Chuanyang Zheng, Yihang Gao, Han Shi, Jing Xiong, Jiankai Sun, Jingyao Li, Minbin Huang, Xiaozhe Ren, Michael K. Ng, Xin Jiang, Zhenguo Li, Yu Li
2024 A* conf
DAPE: Data-Adaptive Positional Encoding for Length Extrapolation.
NeurIPS
Chuanyang Zheng, Yihang Gao, Han Shi, Minbin Huang, Jingyao Li, Jing Xiong, Xiaozhe Ren, Michael K. Ng, Xin Jiang, Zhenguo Li, Yu Li
2024 J jnl
On the Convergence of (Stochastic) Gradient Descent for Kolmogorov-Arnold Networks.
CoRR
Yihang Gao, Vincent Y. F. Tan
2024 J jnl
On the Expressive Power of a Variant of the Looped Transformer.
CoRR
Yihang Gao, Chuanyang Zheng, Enze Xie, Han Shi, Tianyang Hu, Yu Li, Michael K. Ng, Zhenguo Li, Zhaoqiang Liu
2024 J jnl
SepLLM: Accelerate Large Language Models by Compressing One Segment into One Separator.
CoRR
Guoxuan Chen, Han Shi, Jiawei Li, Yihang Gao, Xiaozhe Ren, Yimeng Chen, Xin Jiang, Zhenguo Li, Weiyang Liu, Chao Huang
2024 — conf
Super-resolved Estimation of White Matter Microstructure via 3D Conditional Latent Diffusion Model.
BIBM
Jiquan Ma, Yihang Gao, Haotian Jiang, Jing Gu, Diliara Khairullina, Hui Cui, Geng Chen
2023 J jnl
Approximating Probability Distributions by Using Wasserstein Generative Adversarial Networks.
SIAM J. Math. Data Sci.
Yihang Gao, Michael K. Ng, Mingjie Zhou
2023 A* conf
Gradient Descent Finds the Global Optima of Two-Layer Physics-Informed Neural Networks.
ICML
Yihang Gao, Yiqi Gu, Michael Ng
2022 J jnl
A Momentum Accelerated Adaptive Cubic Regularization Method for Nonconvex Optimization.
CoRR
Yihang Gao, Michael Kwok-Po Ng
2022 A* conf
Approximate Secular Equations for the Cubic Regularization Subproblem.
NeurIPS
Yihang Gao, Man-Chung Yue, Michael Ng
2022 J jnl
Approximate Secular Equations for the Cubic Regularization Subproblem.
CoRR
Yihang Gao, Man-Chung Yue, Michael Kwok-Po Ng
2022 J jnl
HessianFR: An Efficient Hessian-based Follow-the-Ridge Algorithm for Minimax Optimization.
CoRR
Yihang Gao, Huafeng Liu, Michael K. Ng, Mingjie Zhou
2022 — conf
SVD-PINNs: Transfer Learning of Physics-Informed Neural Networks via Singular Value Decomposition.
SSCI
Yihang Gao, Ka Chun Cheung, Michael K. Ng
2022 J jnl
SVD-PINNs: Transfer Learning of Physics-Informed Neural Networks via Singular Value Decomposition.
CoRR
Yihang Gao, Ka Chun Cheung, Michael K. Ng
2022 J jnl
Wasserstein generative adversarial uncertainty quantification in physics-informed neural networks.
J. Comput. Phys.
Yihang Gao, Michael K. Ng
2021 J jnl
Approximation for Probability Distributions by Wasserstein GAN.
CoRR
Yihang Gao, Michael K. Ng
2021 — conf
Research on Sentiment Dictionary Based on Sentiment Analysis in News Domain.
BigDataSecurity
Yihang Gao, Peng Su, Hui Zhao, Meikang Qiu, Meiqin Liu
2021 J jnl
Wasserstein Generative Adversarial Uncertainty Quantification in Physics-Informed Neural Networks.
CoRR
Yihang Gao, Michael K. Ng
2020 — conf
An Improved News Recommendation Algorithm Based on Text Similarity.
SmartBlock
Yihang Gao, Hui Zhao, Qian Zhou, Meikang Qiu, Meiqin Liu