Chen, Yilan

7 publications

NeurIPS 2025 Generalization Bound of Gradient Flow Through Training Trajectory and Data-Dependent Kernel Yilan Chen, Zhichao Wang, Wei Huang, Andi Han, Taiji Suzuki, Arya Mazumdar

NeurIPS 2025 How Does Label Noise Gradient Descent Improve Generalization in the Low SNR Regime? Wei Huang, Andi Han, Yujin Song, Yilan Chen, Denny Wu, Difan Zou, Taiji Suzuki

ICML 2024 On the Emergence of Cross-Task Linearity in Pretraining-Finetuning Paradigm Zhanpeng Zhou, Zijun Chen, Yilan Chen, Bo Zhang, Junchi Yan

NeurIPS 2024 Provable and Efficient Dataset Distillation for Kernel Ridge Regression Yilan Chen, Wei Huang, Tsui-Wei Weng

TMLR 2023 Analyzing Deep PAC-Bayesian Learning with Neural Tangent Kernel: Convergence, Analytic Generalization Bound, and Efficient Hyperparameter Selection Wei Huang, Chunrui Liu, Yilan Chen, Richard Yi Da Xu, Miao Zhang, Tsui-Wei Weng

NeurIPS 2023 Analyzing Generalization of Neural Networks Through Loss Path Kernels Yilan Chen, Wei Huang, Hao Wang, Charlotte Loh, Akash Srivastava, Lam Nguyen, Lily Weng

NeurIPS 2021 On the Equivalence Between Neural Network and Support Vector Machine Yilan Chen, Wei Huang, Lam Nguyen, Tsui-Wei Weng