256 citations · 655 across the 51 of their papers we have counts for
3 papers · 2 filters
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}) = \…
When is a Convolutional Filter Easy To Learn?
Simon S. Du, Jason D. Lee, Yuandong Tian
We analyze the convergence of (stochastic) gradient descent algorithm for learning a convolutional filter with Rectified Linear Unit (ReLU) activation function. Our analysis does n…
Stochastic Variance Reduction Methods for Policy Evaluation
Simon S. Du, Jianshu Chen, Lihong Li +2
Policy evaluation is a crucial step in many reinforcement-learning procedures, which estimates a value function that predicts states' long-term value under a given policy. In this…