39 citations · 124 across the 17 of their papers we have counts for
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cs.LG2018★ 4 cited
A Geometric Approach of Gradient Descent Algorithms in Linear Neural Networks
Yacine Chitour, Zhenyu Liao, Romain Couillet
In this paper, we propose a geometric framework to analyze the convergence properties of gradient descent trajectories in the context of linear neural networks. We translate a well…
stat.ML2018★ 21 cited
The Dynamics of Learning: A Random Matrix Approach
Zhenyu Liao, Romain Couillet
Understanding the learning dynamics of neural networks is one of the key issues for the improvement of optimization algorithms as well as for the theoretical comprehension of why d…
stat.ML2018★ 4 cited
On the Spectrum of Random Features Maps of High Dimensional Data
Zhenyu Liao, Romain Couillet
Random feature maps are ubiquitous in modern statistical machine learning, where they generalize random projections by means of powerful, yet often difficult to analyze nonlinear o…