28 citations · 120 across the 12 of their papers we have counts for
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cs.LG2022★ 1 cited
A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning
Zixiang Chen, Chris Junchi Li, Angela Yuan +2
With the increasing need for handling large state and action spaces, general function approximation has become a key technique in reinforcement learning (RL). In this paper, we pro…
cs.LG2022★ 23 cited
Towards Understanding Mixture of Experts in Deep Learning
Zixiang Chen, Yihe Deng, Yue Wu +2
The Mixture-of-Experts (MoE) layer, a sparsely-activated model controlled by a router, has achieved great success in deep learning. However, the understanding of such architecture…
cs.LG2022★ 20 cited
Benign Overfitting in Two-layer Convolutional Neural Networks
Yuan Cao, Zixiang Chen, Mikhail Belkin +1
Modern neural networks often have great expressive power and can be trained to overfit the training data, while still achieving a good test performance. This phenomenon is referred…