Approximate is Good Enough: Probabilistic Variants of Dimensional and Margin Complexity

9 March 2020

Papers citing "Approximate is Good Enough: Probabilistic Variants of Dimensional and Margin Complexity"

5 / 5 papers shown

Title
What Can ResNet Learn Efficiently, Going Beyond Kernels? Zeyuan Allen-Zhu Yuanzhi Li 390 183 0 24 May 2019
On the Power and Limitations of Random Features for Understanding Neural Networks Gilad Yehudai Ohad Shamir MLT 77 182 0 01 Apr 2019
Neural Tangent Kernel: Convergence and Generalization in Neural Networks Arthur Jacot Franck Gabriel Clément Hongler 267 3,195 0 20 Jun 2018
SGD Learns the Conjugate Kernel Class of the Network Amit Daniely 186 181 0 27 Feb 2017
Super-Linear Gate and Super-Quadratic Wire Lower Bounds for Depth-Two and Depth-Three Threshold Circuits D. Kane Ryan Williams 36 61 0 24 Nov 2015