Principled Deep Neural Network Training through Linear Programming

7 October 2018

Papers citing "Principled Deep Neural Network Training through Linear Programming"

7 / 7 papers shown

Title
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 94 32 0 29 Apr 2023
Globally Optimal Training of Neural Networks with Threshold Activation Functions Tolga Ergen Halil Ibrahim Gulluk Jonathan Lacotte Mert Pilanci 68 8 0 06 Mar 2023
$Training Fully Connected Neural Networks is $\exists\mathbb{R}$-Complete$ Training Fully Connected Neural Networks is $\exists\mathbb{R}$ -Complete Daniel Bertschinger Christoph Hertrich Paul Jungeblut Tillmann Miltzow Simon Weber OffRL 59 30 0 04 Apr 2022
Parallel Successive Learning for Dynamic Distributed Model Training over Heterogeneous Wireless Networks Seyyedali Hosseinalipour Su Wang Nicolò Michelusi Vaneet Aggarwal Christopher G. Brinton David J. Love M. Chiang 23 27 0 07 Feb 2022
Training Thinner and Deeper Neural Networks: Jumpstart Regularization Carles Roger Riera Molina Camilo Rey Thiago Serra Eloi Puertas O. Pujol 27 4 0 30 Jan 2022
Neural networks with linear threshold activations: structure and algorithms Sammy Khalife Hongyu Cheng A. Basu 42 14 0 15 Nov 2021
Input Convex Neural Networks Brandon Amos Lei Xu J. Zico Kolter 187 599 0 22 Sep 2016