4 citations · 4 across the 2 of their papers we have counts for
4 papers
Pointwise Generalization in Deep Neural Networks
Shaojie Li, Yunbei Xu
We address the fundamental question of why deep neural networks generalize by establishing a pointwise generalization theory for fully connected networks. This framework resolves l…
Improved Learning Rates for Stochastic Optimization
Shaojie Li, Pengwei Tang, Yong Liu
Stochastic optimization is a cornerstone of modern machine learning. This paper studies the generalization performance of two classical stochastic optimization algorithms: stochast…
Stability and Sharper Risk Bounds with Convergence Rate
Bowei Zhu, Shaojie Li, Mingyang Yi +1
Prior work (Klochkov Zhivotovskiy, 2021) establishes at most excess risk bounds via algorithmic stability for strongly-convex learners with high pro…
Towards Sharper Risk Bounds for Minimax Problems
Bowei Zhu, Shaojie Li, Yong Liu
Minimax problems have achieved success in machine learning such as adversarial training, robust optimization, reinforcement learning. For theoretical analysis, current optimal exce…