Optimization Methods for Supervised Machine Learning: From Linear Models to Deep Learning

30 June 2017

Papers citing "Optimization Methods for Supervised Machine Learning: From Linear Models to Deep Learning"

8 / 8 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
First-Order Methods for Convex Optimization Pavel Dvurechensky Mathias Staudigl Shimrit Shtern ODL 31 25 0 04 Jan 2021
Adaptive Stochastic Optimization Frank E. Curtis K. Scheinberg ODL 13 29 0 18 Jan 2020
Optimization for deep learning: theory and algorithms Ruoyu Sun ODL 19 168 0 19 Dec 2019
Optimization Problems for Machine Learning: A Survey Claudio Gambella Bissan Ghaddar Joe Naoum-Sawaya AI4CE 30 178 0 16 Jan 2019
Predicting Tactical Solutions to Operational Planning Problems under Imperfect Information Eric Larsen Sébastien Lachapelle Yoshua Bengio Emma Frejinger Simon Lacoste-Julien Andrea Lodi 25 46 0 31 Jul 2018
Proximal Gradient Method with Extrapolation and Line Search for a Class of Nonconvex and Nonsmooth Problems Lei Yang 35 23 0 18 Nov 2017
Optimization Methods for Large-Scale Machine Learning Léon Bottou Frank E. Curtis J. Nocedal 22 3,172 0 15 Jun 2016