NIPS Proceedings
^{β}
Books
Simon S. Du
11 Papers
Acceleration via Symplectic Discretization of High-Resolution Differential Equations
(2019)
Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels
(2019)
On Exact Computation with an Infinitely Wide Neural Net
(2019)
Provably Efficient Q-learning with Function Approximation via Distribution Shift Error Checking Oracle
(2019)
Towards Understanding the Importance of Shortcut Connections in Residual Networks
(2019)
Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced
(2018)
How Many Samples are Needed to Estimate a Convolutional Neural Network?
(2018)
Gradient Descent Can Take Exponential Time to Escape Saddle Points
(2017)
Hypothesis Transfer Learning via Transformation Functions
(2017)
On the Power of Truncated SVD for General High-rank Matrix Estimation Problems
(2017)
Efficient Nonparametric Smoothness Estimation
(2016)