Kou, Yiwen

11 publications

TMLR 2025 Guided Discrete Diffusion for Electronic Health Record Generation Jun Han, Zixiang Chen, Yongqian Li, Yiwen Kou, Eran Halperin, Robert E. Tillman, Quanquan Gu

AISTATS 2025 On the Power of Multitask Representation Learning with Gradient Descent Qiaobo Li, Zixiang Chen, Yihe Deng, Yiwen Kou, Yuan Cao, Quanquan Gu

NeurIPS 2025 Smoothed Agnostic Learning of Halfspaces over the Hypercube Yiwen Kou, Raghu Meka

NeurIPS 2024 Fast Sampling via Discrete Non-Markov Diffusion Models with Predetermined Transition Time Zixiang Chen, Huizhuo Yuan, Yongqian Li, Yiwen Kou, Junkai Zhang, Quanquan Gu

NeurIPS 2024 GraphVis: Boosting LLMs with Visual Knowledge Graph Integration Yihe Deng, Chenchen Ye, Zijie Huang, Mingyu Derek Ma, Yiwen Kou, Wei Wang

NeurIPS 2024 Matching the Statistical Query Lower Bound for $k$-Sparse Parity Problems with Sign Stochastic Gradient Descent Yiwen Kou, Zixiang Chen, Quanquan Gu, Sham M. Kakade

ICML 2023 Benign Overfitting in Two-Layer ReLU Convolutional Neural Networks Yiwen Kou, Zixiang Chen, Yuanzhou Chen, Quanquan Gu

ICLR 2023 How Does Semi-Supervised Learning with Pseudo-Labelers Work? a Case Study Yiwen Kou, Zixiang Chen, Yuan Cao, Quanquan Gu

NeurIPS 2023 Implicit Bias of Gradient Descent for Two-Layer ReLU and Leaky ReLU Networks on Nearly-Orthogonal Data Yiwen Kou, Zixiang Chen, Quanquan Gu

NeurIPS 2023 Why Does Sharpness-Aware Minimization Generalize Better than SGD? Zixiang Chen, Junkai Zhang, Yiwen Kou, Xiangning Chen, Cho-Jui Hsieh, Quanquan Gu

ICML 2022 Certified Adversarial Robustness Under the Bounded Support Set Yiwen Kou, Qinyuan Zheng, Yisen Wang