565 citations · 1.2k across the 15 of their papers we have counts for
5 papers · 1 filter
Synthetic Principal Component Design: Fast Covariate Balancing with Synthetic Controls
Yiping Lu, Jiajin Li, Lexing Ying +1
The optimal design of experiments typically involves solving an NP-hard combinatorial optimization problem. In this paper, we aim to develop a globally convergent and practically e…
Importance Tempering: Group Robustness for Overparameterized Models
Yiping Lu, Wenlong Ji, Zachary Izzo +1
Although overparameterized models have shown their success on many machine learning tasks, the accuracy could drop on the testing distribution that is different from the training o…
Minimax Optimal Kernel Operator Learning via Multilevel Training
Jikai Jin, Yiping Lu, Jose Blanchet +1
Learning mappings between infinite-dimensional function spaces has achieved empirical success in many disciplines of machine learning, including generative modeling, functional dat…
Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks
Huishuai Zhang, Da Yu, Yiping Lu +1
Adversarial examples, which are usually generated for specific inputs with a specific model, are ubiquitous for neural networks. In this paper we unveil a surprising property of ad…
Sobolev Acceleration and Statistical Optimality for Learning Elliptic Equations via Gradient Descent
Yiping Lu, Jose Blanchet, Lexing Ying
In this paper, we study the statistical limits in terms of Sobolev norms of gradient descent for solving inverse problem from randomly sampled noisy observations using a general cl…