Li, Hongkang

15 publications

NeurIPS 2025 Contrastive Learning with Data Misalignment: Feature Purity, Training Dynamics and Theoretical Generalization Guarantees Jiawei Sun, Shuai Zhang, Hongkang Li, Meng Wang

ICLR 2025 Node Identifiers: Compact, Discrete Representations for Efficient Graph Learning Yuankai Luo, Hongkang Li, Qijiong Liu, Lei Shi, Xiao-Ming Wu

TMLR 2025 Theoretical Learning Performance of Graph Networks: The Impact of Jumping Connections and Layer-Wise Sparsification Jiawei Sun, Hongkang Li, Meng Wang

ICLR 2025 Training Nonlinear Transformers for Chain-of-Thought Inference: A Theoretical Generalization Analysis Hongkang Li, Songtao Lu, Pin-Yu Chen, Xiaodong Cui, Meng Wang

ICLR 2025 When Is Task Vector Provably Effective for Model Editing? a Generalization Analysis of Nonlinear Transformers Hongkang Li, Yihua Zhang, Shuai Zhang, Pin-Yu Chen, Sijia Liu, Meng Wang

NeurIPS 2024 Enhancing Graph Transformers with Hierarchical Distance Structural Encoding Yuankai Luo, Hongkang Li, Lei Shi, Xiao-Ming Wu

ICMLW 2024 How Do Nonlinear Transformers Acquire Generalization-Guaranteed CoT Ability? Hongkang Li, Meng Wang, Songtao Lu, Xiaodong Cui, Pin-Yu Chen

ICMLW 2024 How Do Nonlinear Transformers Acquire Generalization-Guaranteed CoT Ability? Hongkang Li, Meng Wang, Songtao Lu, Xiaodong Cui, Pin-Yu Chen

ICML 2024 How Do Nonlinear Transformers Learn and Generalize in In-Context Learning? Hongkang Li, Meng Wang, Songtao Lu, Xiaodong Cui, Pin-Yu Chen

ICML 2024 What Improves the Generalization of Graph Transformers? a Theoretical Dive into the Self-Attention and Positional Encoding Hongkang Li, Meng Wang, Tengfei Ma, Sijia Liu, Zaixi Zhang, Pin-Yu Chen

ICLR 2023 A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen

NeurIPS 2023 On the Convergence and Sample Complexity Analysis of Deep Q-Networks with $\epsilon$-Greedy Exploration Shuai Zhang, Hongkang Li, Meng Wang, Miao Liu, Pin-Yu Chen, Songtao Lu, Sijia Liu, Keerthiram Murugesan, Subhajit Chaudhury

NeurIPSW 2023 Transformers as Multi-Task Feature Selectors: Generalization Analysis of In-Context Learning Hongkang Li, Meng Wang, Songtao Lu, Hui Wan, Xiaodong Cui, Pin-Yu Chen

NeurIPSW 2023 What Improves the Generalization of Graph Transformer? a Theoretical Dive into Self-Attention and Positional Encoding Hongkang Li, Meng Wang, Tengfei Ma, Sijia Liu, Zaixi Zhang, Pin-Yu Chen

ICML 2022 Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong