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2020 – today
- 2024
[i6]Zixiang Chen, Jun Han, Yongqian Li, Yiwen Kou, Eran Halperin, Robert E. Tillman, Quanquan Gu:
Guided Discrete Diffusion for Electronic Health Record Generation. CoRR abs/2404.12314 (2024)- [i5]Yiwen Kou, Zixiang Chen, Quanquan Gu, Sham M. Kakade:
Matching the Statistical Query Lower Bound for k-sparse Parity Problems with Stochastic Gradient Descent. CoRR abs/2404.12376 (2024) - 2023
- [c5]Yiwen Kou, Zixiang Chen, Yuan Cao, Quanquan Gu:
How Does Semi-supervised Learning with Pseudo-labelers Work? A Case Study. ICLR 2023 - [c4]Yiwen Kou, Zixiang Chen, Yuanzhou Chen, Quanquan Gu:
Benign Overfitting in Two-layer ReLU Convolutional Neural Networks. ICML 2023: 17615-17659 - [c3]Zixiang Chen, Junkai Zhang, Yiwen Kou, Xiangning Chen, Cho-Jui Hsieh, Quanquan Gu:
Why Does Sharpness-Aware Minimization Generalize Better Than SGD? NeurIPS 2023 - [c2]Yiwen Kou, Zixiang Chen, Quanquan Gu:
Implicit Bias of Gradient Descent for Two-layer ReLU and Leaky ReLU Networks on Nearly-orthogonal Data. NeurIPS 2023 - [i4]Yiwen Kou, Zixiang Chen, Yuanzhou Chen, Quanquan Gu:
Benign Overfitting for Two-layer ReLU Networks. CoRR abs/2303.04145 (2023) - [i3]Zixiang Chen, Junkai Zhang, Yiwen Kou, Xiangning Chen, Cho-Jui Hsieh, Quanquan Gu:
Why Does Sharpness-Aware Minimization Generalize Better Than SGD? CoRR abs/2310.07269 (2023) - [i2]Yiwen Kou, Zixiang Chen, Quanquan Gu:
Implicit Bias of Gradient Descent for Two-layer ReLU and Leaky ReLU Networks on Nearly-orthogonal Data. CoRR abs/2310.18935 (2023) - [i1]Zixiang Chen, Huizhuo Yuan, Yongqian Li, Yiwen Kou, Junkai Zhang, Quanquan Gu:
Fast Sampling via De-randomization for Discrete Diffusion Models. CoRR abs/2312.09193 (2023) - 2022
- [c1]Yiwen Kou, Qinyuan Zheng, Yisen Wang:
Certified Adversarial Robustness Under the Bounded Support Set. ICML 2022: 11559-11597
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