365 citations · 452 across the 4 of their papers we have counts for
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cs.LG2017★ 20 cited
Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima
Simon S. Du, Jason D. Lee, Yuandong Tian +2
We consider the problem of learning a one-hidden-layer neural network with non-overlapping convolutional layer and ReLU activation, i.e., $f(\mathbf{Z}, \mathbf{w}, \mathbf{a}) = \…
math.OC2017★ 62 cited
Gradient Descent Can Take Exponential Time to Escape Saddle Points
Simon S. Du, Chi Jin, Jason D. Lee +3
Although gradient descent (GD) almost always escapes saddle points asymptotically [Lee et al., 2016], this paper shows that even with fairly natural random initialization schemes a…