Han Yang

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 18

Top Topics

Risk Minimization

Top Venues

Publications

Kaili Ma, Han Yang, Shanchao Yang, Kangfei Zhao, Lanqing Li, Yongqiang Chen, Junzhou Huang, James Cheng, Yu Rong
Solving the non-submodular network collapse problems via Decision Transformer. Neural Networks 176 (2024)
Kaili Ma, Garry Yang, Han Yang, Yongqiang Chen, James Cheng
Calibrating and Improving Graph Contrastive Learning. Trans. Mach. Learn. Res. 2023 (2023)
Yuntao Gui, Xiao Yan, Peiqi Yin, Han Yang, James Cheng
SPT: Fine-Tuning Transformer-based Language Models Efficiently with Sparsification. CoRR (2023)
Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Bingzhe Wu, Yonggang Zhang, Kaili Ma, Han Yang, Peilin Zhao, Bo Han, James Cheng
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization. ICLR (2023)
Barakeel Fanseu Kamhoua, Lin Zhang, Yongqiang Chen, Han Yang, Kaili Ma, Bo Han, Bo Li, James Cheng
Exact Shape Correspondence via 2D graph convolution. NeurIPS (2022)
Yongqiang Chen, Han Yang, Yonggang Zhang, Kaili Ma, Tongliang Liu, Bo Han, James Cheng
Understanding and Improving Graph Injection Attack by Promoting Unnoticeability. ICLR (2022)
Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Kaili Ma, Yonggang Zhang, Han Yang, Bo Han, James Cheng
Pareto Invariant Risk Minimization. CoRR (2022)
Yuntao Gui, Yidi Wu, Han Yang, Tatiana Jin, Boyang Li, Qihui Zhou, James Cheng, Fan Yu
HGL: Accelerating Heterogeneous GNN Training with Holistic Representation and Optimization. SC (2022)
Yongqiang Chen, Yonggang Zhang, Yatao Bian, Han Yang, Kaili Ma, Binghui Xie, Tongliang Liu, Bo Han, James Cheng
Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs. NeurIPS (2022)
Yongqiang Chen, Yonggang Zhang, Han Yang, Kaili Ma, Binghui Xie, Tongliang Liu, Bo Han, James Cheng
Invariance Principle Meets Out-of-Distribution Generalization on Graphs. CoRR (2022)
Han Yang, Xiao Yan, Xinyan Dai, Yongqiang Chen, James Cheng
Self-Enhanced GNN: Improving Graph Neural Networks Using Model Outputs. IJCNN (2021)
Han Yang, Kaili Ma, James Cheng
Rethinking Graph Regularization for Graph Neural Networks. AAAI (2021)
Kaili Ma, Haochen Yang, Han Yang, Tatiana Jin, Pengfei Chen, Yongqiang Chen, Barakeel Fanseu Kamhoua, James Cheng
Improving Graph Representation Learning by Contrastive Regularization. CoRR (2021)
Han Yang, Xiao Yan, Xinyan Dai, James Cheng
Self-Enhanced GNN: Improving Graph Neural Networks Using Model Outputs. CoRR (2020)
Xinyan Dai, Xiao Yan, Kaiwen Zhou, Yuxuan Wang, Han Yang, James Cheng
Convolutional Embedding for Edit Distance. SIGIR (2020)
Han Yang, Kaili Ma, James Cheng
Rethinking Graph Regularization For Graph Neural Networks. CoRR (2020)
Xinyan Dai, Xiao Yan, Kaiwen Zhou, Yuxuan Wang, Han Yang, James Cheng
Edit Distance Embedding using Convolutional Neural Networks. CoRR (2020)
Xinyan Dai, Xiao Yan, Kaiwen Zhou, Han Yang, Kelvin Kai Wing Ng, James Cheng, Yu Fan
Hyper-Sphere Quantization: Communication-Efficient SGD for Federated Learning. CoRR (2019)