19 citations · 19 across the 4 of their papers we have counts for
4 papers · 1 filter
Algorithmic Separation between Constant-Depth and Logarithmic-Depth Neural Networks
Yunwei Ren, Zihao Wang, Jason D. Lee
Despite the empirical advantages of deep networks over shallow ones, theoretical depth separations largely concern approximation power, while algorithmic results are mostly limited…
Phase Transitions for Feature Learning in Neural Networks
Andrea Montanari, Zihao Wang
According to a popular viewpoint, neural networks learn from data by first identifying low-dimensional representations, and subsequently fitting the best model in this space. Recen…
Learning Hierarchical Polynomials of Multiple Nonlinear Features with Three-Layer Networks
Hengyu Fu, Zihao Wang, Eshaan Nichani +1
In deep learning theory, a critical question is to understand how neural networks learn hierarchical features. In this work, we study the learning of hierarchical polynomials of \t…
PSNE: Efficient Spectral Sparsification Algorithms for Scaling Network Embedding
Longlong Lin, Yunfeng Yu, Zihao Wang +4
Network embedding has numerous practical applications and has received extensive attention in graph learning, which aims at mapping vertices into a low-dimensional and continuous d…