Adaptive and Oblivious Randomized Subspace Methods for High-Dimensional Optimization: Sharp Analysis and Lower Bounds

13 December 2020

Papers citing "Adaptive and Oblivious Randomized Subspace Methods for High-Dimensional Optimization: Sharp Analysis and Lower Bounds"

6 / 6 papers shown

Title
When Do Neural Networks Outperform Kernel Methods? Behrooz Ghorbani Song Mei Theodor Misiakiewicz Andrea Montanari 76 188 0 24 Jun 2020
Neural Networks are Convex Regularizers: Exact Polynomial-time Convex Optimization Formulations for Two-layer Networks Mert Pilanci Tolga Ergen 61 118 0 24 Feb 2020
Revealing the Structure of Deep Neural Networks via Convex Duality Tolga Ergen Mert Pilanci MLT 38 71 0 22 Feb 2020
Optimal Randomized First-Order Methods for Least-Squares Problems Jonathan Lacotte Mert Pilanci 43 30 0 21 Feb 2020
Reverse iterative volume sampling for linear regression Michal Derezinski Manfred K. Warmuth 66 43 0 06 Jun 2018
How transferable are features in deep neural networks? J. Yosinski Jeff Clune Yoshua Bengio Hod Lipson OOD 148 8,309 0 06 Nov 2014