12 citations · 39 across the 12 of their papers we have counts for
4 papers · 1 filter
Beyond Lazy Training for Over-parameterized Tensor Decomposition
Xiang Wang, Chenwei Wu, Jason D. Lee +2
Over-parametrization is an important technique in training neural networks. In both theory and practice, training a larger network allows the optimization algorithm to avoid bad lo…
Dissecting Hessian: Understanding Common Structure of Hessian in Neural Networks
Yikai Wu, Xingyu Zhu, Chenwei Wu +2
Hessian captures important properties of the deep neural network loss landscape. Previous works have observed low rank structure in the Hessians of neural networks. In this paper,…
Secure Data Sharing With Flow Model
Chenwei Wu, Chenzhuang Du, Yang Yuan
In the classical multi-party computation setting, multiple parties jointly compute a function without revealing their own input data. We consider a variant of this problem, where t…
Guarantees for Tuning the Step Size using a Learning-to-Learn Approach
Xiang Wang, Shuai Yuan, Chenwei Wu +1
Choosing the right parameters for optimization algorithms is often the key to their success in practice. Solving this problem using a learning-to-learn approach -- using meta-gradi…