The Computational Complexity of ReLU Network Training Parameterized by Data Dimensionality

18 May 2021

Papers citing "The Computational Complexity of ReLU Network Training Parameterized by Data Dimensionality"

5 / 5 papers shown

Title
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 129 37 0 29 Apr 2023
Tight Hardness Results for Training Depth-2 ReLU Networks Surbhi Goel Adam R. Klivans Pasin Manurangsi Daniel Reichman 54 41 0 27 Nov 2020
Neural Networks are Convex Regularizers: Exact Polynomial-time Convex Optimization Formulations for Two-layer Networks Mert Pilanci Tolga Ergen 69 118 0 24 Feb 2020
Learning Two Layer Rectified Neural Networks in Polynomial Time Ainesh Bakshi Rajesh Jayaram David P. Woodruff NoLa 151 69 0 05 Nov 2018
On Loss Functions for Deep Neural Networks in Classification Katarzyna Janocha Wojciech M. Czarnecki UQCV 68 549 0 18 Feb 2017