Yiping Lu

According to our database, Yiping Lu authored at least 21 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty.

Kaizhao Liu, José H. Blanchet, Lexing Ying, Yiping Lu

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Statistical Spatially Inhomogeneous Diffusion Inference.

Yinuo Ren, Yiping Lu, Lexing Ying, Grant M. Rotskoff

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

When can Regression-Adjusted Control Variates Help? Rare Events, Sobolev Embedding and Minimax Optimality.

Jose H. Blanchet, Haoxuan Chen, Yiping Lu, Lexing Ying

CoRR, 2023

When can Regression-Adjusted Control Variate Help? Rare Events, Sobolev Embedding and Minimax Optimality.

Jose H. Blanchet, Haoxuan Chen, Yiping Lu, Lexing Ying

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Minimax Optimal Kernel Operator Learning via Multilevel Training.

Jikai Jin, Yiping Lu, José H. Blanchet, Lexing Ying

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks.

Huishuai Zhang, Da Yu, Yiping Lu, Di He

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Synthetic Principal Component Design: Fast Covariate Balancing with Synthetic Controls.

Yiping Lu, Jiajin Li, Lexing Ying, Jose H. Blanchet

CoRR, 2022

Importance Tempering: Group Robustness for Overparameterized Models.

Yiping Lu, Wenlong Ji, Zachary Izzo, Lexing Ying

CoRR, 2022

Sobolev Acceleration and Statistical Optimality for Learning Elliptic Equations via Gradient Descent.

Yiping Lu, José H. Blanchet, Lexing Ying

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

An Unconstrained Layer-Peeled Perspective on Neural Collapse.

Wenlong Ji, Yiping Lu, Yiliang Zhang, Zhun Deng, Weijie J. Su

Proceedings of the Tenth International Conference on Learning Representations, 2022

Machine Learning For Elliptic PDEs: Fast Rate Generalization Bound, Neural Scaling Law and Minimax Optimality.

Yiping Lu, Haoxuan Chen, Jianfeng Lu, Lexing Ying, Jose H. Blanchet

Proceedings of the Tenth International Conference on Learning Representations, 2022

2020

CURE: Curvature Regularization for Missing Data Recovery.

Bin Dong, Haocheng Ju, Yiping Lu, Zuoqiang Shi

SIAM J. Imaging Sci., 2020

A Mean-field Analysis of Deep ResNet and Beyond: Towards Provable Optimization Via Overparameterization From Depth.

Yiping Lu, Chao Ma, Yulong Lu, Jianfeng Lu, Lexing Ying

CoRR, 2020

A Mean Field Analysis Of Deep ResNet And Beyond: Towards Provably Optimization Via Overparameterization From Depth.

Yiping Lu, Chao Ma, Yulong Lu, Jianfeng Lu, Lexing Ying

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

PDE-Net 2.0: Learning PDEs from data with a numeric-symbolic hybrid deep network.

Zichao Long, Yiping Lu, Bin Dong

J. Comput. Phys., 2019

Distillation ≈ Early Stopping? Harvesting Dark Knowledge Utilizing Anisotropic Information Retrieval For Overparameterized Neural Network.

Bin Dong, Jikai Hou, Yiping Lu, Zhihua Zhang

CoRR, 2019

Understanding and Improving Transformer From a Multi-Particle Dynamic System Point of View.

Yiping Lu, Zhuohan Li, Di He, Zhiqing Sun, Bin Dong, Tao Qin, Liwei Wang, Tie-Yan Liu

CoRR, 2019

You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle.

Dinghuai Zhang, Tianyuan Zhang, Yiping Lu, Zhanxing Zhu, Bin Dong

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Dynamically Unfolding Recurrent Restorer: A Moving Endpoint Control Method for Image Restoration.

Xiaoshuai Zhang, Yiping Lu, Jiaying Liu, Bin Dong

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations.

Yiping Lu, Aoxiao Zhong, Quanzheng Li, Bin Dong

Proceedings of the 35th International Conference on Machine Learning, 2018

PDE-Net: Learning PDEs from Data.

Zichao Long, Yiping Lu, Xianzhong Ma, Bin Dong

Proceedings of the 35th International Conference on Machine Learning, 2018