Improved Training Speed, Accuracy, and Data Utilization Through Loss Function Optimization

27 May 2019

Papers citing "Improved Training Speed, Accuracy, and Data Utilization Through Loss Function Optimization"

14 / 14 papers shown

Title
Effective Regularization Through Loss-Function Metalearning Santiago Gonzalez Xin Qiu Risto Miikkulainen 105 5 0 02 Oct 2020
AutoAugment: Learning Augmentation Policies from Data E. D. Cubuk Barret Zoph Dandelion Mané Vijay Vasudevan Quoc V. Le 118 1,771 0 24 May 2018
The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities Joel Lehman Jeff Clune D. Misevic C. Adami L. Altenberg ... Danesh Tarapore S. Thibault Westley Weimer R. Watson Jason Yosinksi 100 280 0 09 Mar 2018
Evolved Policy Gradients Rein Houthooft Richard Y. Chen Phillip Isola Bradly C. Stadie Filip Wolski Jonathan Ho Pieter Abbeel 81 227 0 13 Feb 2018
Regularized Evolution for Image Classifier Architecture Search Esteban Real A. Aggarwal Yanping Huang Quoc V. Le 150 3,025 0 05 Feb 2018
Evolving Deep Neural Networks Risto Miikkulainen J. Liang Elliot Meyerson Aditya Rawal Daniel Fink ... B. Raju Hormoz Shahrzad Arshak Navruzyan Nigel P. Duffy Babak Hodjat 86 888 0 01 Mar 2017
On Loss Functions for Deep Neural Networks in Classification Katarzyna Janocha Wojciech M. Czarnecki UQCV 68 549 0 18 Feb 2017
Regularizing Neural Networks by Penalizing Confident Output Distributions Gabriel Pereyra George Tucker J. Chorowski Lukasz Kaiser Geoffrey E. Hinton NoLa 153 1,137 0 23 Jan 2017
A General and Adaptive Robust Loss Function Jonathan T. Barron OOD DRL 170 538 0 11 Jan 2017
TensorFlow: A system for large-scale machine learning Martín Abadi P. Barham Jianmin Chen Zhiwen Chen Andy Davis ... Vijay Vasudevan Pete Warden Martin Wicke Yuan Yu Xiaoqiang Zhang GNN AI4CE 415 18,334 0 27 May 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 722 9,290 0 06 Jun 2015
Cyclical Learning Rates for Training Neural Networks L. Smith ODL 181 2,517 0 03 Jun 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.5K 149,842 0 22 Dec 2014
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 432 7,658 0 03 Jul 2012