[PDF] Using Statistics to Automate Stochastic Optimization - NIPS PDF 9150-using-statistics-to-automate-stochastic-optimization.pdf

rate of stochastic gradient methods remains a major roadblock to obtaining good 2011; Tieleman and Hinton, 2012; Kingma and Ba, 2014, and other variants),

18 oct 2015 · Disadvantage in non-stationary settings: All gradients (recent and old) weighted equally Nadav Cohen Adam (Kingma Ba) October 18, 2015

[PDF] pbSGD: Powered Stochastic Gradient Descent Methods for - IJCAI

[Kingma and Ba, 2015] are proposed to train DNN more effi- ciently Despite the methods for stochastic optimization with and without momen- tum; 2) conduct

[PDF] Stochastic Optimization for Machine Learning - Shuai Zheng

This survey provides a review and summary on the stochastic optimization algorithms in the integrate the stochastic gradients into the alternating direction method of multipliers (ADMM), which [40] D Kingma and J Ba Adam: A method

[PDF] Deep Learning - Optimization - Erwan Scornet

Dedicated optimization algorithms can solve this on a large scale very efficiently [“Adam: A method for stochastic optimization”, Kingma and Ba 2014] General

[PDF] Optimizers

Cost function: How good is your neural network? Then: Stochastic gradient descent Adam: A Method for Stochastic Optimization (Kingma Ba, 2015) ○