11 citations · 12 across the 2 of their papers we have counts for
4 papers
Achieving Small Test Error in Mildly Overparameterized Neural Networks
Shiyu Liang, Ruoyu Sun, R. Srikant
Recent theoretical works on over-parameterized neural nets have focused on two aspects: optimization and generalization. Many existing works that study optimization and generalizat…
Revisiting Landscape Analysis in Deep Neural Networks: Eliminating Decreasing Paths to Infinity
Shiyu Liang, Ruoyu Sun, R. Srikant
Traditional landscape analysis of deep neural networks aims to show that no sub-optimal local minima exist in some appropriate sense. From this, one may be tempted to conclude that…
Adding One Neuron Can Eliminate All Bad Local Minima
Shiyu Liang, Ruoyu Sun, Jason D. Lee +1
One of the main difficulties in analyzing neural networks is the non-convexity of the loss function which may have many bad local minima. In this paper, we study the landscape of n…
Understanding the Loss Surface of Neural Networks for Binary Classification
Shiyu Liang, Ruoyu Sun, Yixuan Li +1
It is widely conjectured that the reason that training algorithms for neural networks are successful because all local minima lead to similar performance, for example, see (LeCun e…