PipeTune: Pipeline Parallelism of Hyper and System Parameters Tuning for
Deep Learning Clusters

PipeTune: Pipeline Parallelism of Hyper and System Parameters Tuning for Deep Learning Clusters

1 October 2020

Nathaniel Morris

Papers citing "PipeTune: Pipeline Parallelism of Hyper and System Parameters Tuning for Deep Learning Clusters"

19 / 19 papers shown

Title
Hop: Heterogeneity-Aware Decentralized Training Qinyi Luo Jinkun Lin Youwei Zhuo Xuehai Qian 38 51 0 04 Feb 2019
Parallax: Sparsity-aware Data Parallel Training of Deep Neural Networks Soojeong Kim Gyeong-In Yu Hojin Park Sungwoo Cho Eunji Jeong Hyeonmin Ha Sanha Lee Joo Seong Jeong Byung-Gon Chun 44 75 0 08 Aug 2018
Tune: A Research Platform for Distributed Model Selection and Training Richard Liaw Eric Liang Robert Nishihara Philipp Moritz Joseph E. Gonzalez Ion Stoica 209 901 0 13 Jul 2018
Auto-Keras: An Efficient Neural Architecture Search System Haifeng Jin Qingquan Song Xia Hu 102 808 0 27 Jun 2018
BigDL: A Distributed Deep Learning Framework for Big Data J. Dai Yiheng Wang Xin Qiu Ding Ding Yao Zhang ... Bowen She Dongjie Shi Qiaoling Lu Kai-Qi Huang Guoqiong Song FedML MoE 36 101 0 16 Apr 2018
Population Based Training of Neural Networks Max Jaderberg Valentin Dalibard Simon Osindero Wojciech M. Czarnecki Jeff Donahue ... Tim Green Iain Dunning Karen Simonyan Chrisantha Fernando Koray Kavukcuoglu 79 741 0 27 Nov 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 283 8,883 0 25 Aug 2017
Learning Transferable Architectures for Scalable Image Recognition Barret Zoph Vijay Vasudevan Jonathon Shlens Quoc V. Le 174 5,603 0 21 Jul 2017
ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models Minsuk Kahng Pierre Yves Andrews Aditya Kalro Duen Horng Chau HAI 69 324 0 06 Apr 2017
A Genetic Programming Approach to Designing Convolutional Neural Network Architectures Masanori Suganuma Shinichi Shirakawa T. Nagao 96 592 0 03 Apr 2017
Deep Reinforcement Learning: An Overview Yuxi Li OffRL VLM 169 1,539 0 25 Jan 2017
Variational Dropout Sparsifies Deep Neural Networks Dmitry Molchanov Arsenii Ashukha Dmitry Vetrov BDL 141 830 0 19 Jan 2017
Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization Lisha Li Kevin Jamieson Giulia DeSalvo Afshin Rostamizadeh Ameet Talwalkar 222 2,329 0 21 Mar 2016
An Empirical Evaluation of Deep Learning on Highway Driving Brody Huval Tao Wang S. Tandon Jeff Kiske W. Song ... Toki Migimatsu Royce Cheng-Yue Fernando A. Mujica Adam Coates A. Ng 91 604 0 07 Apr 2015
Hyperparameter Search in Machine Learning Marc Claesen B. De Moor 60 440 0 07 Feb 2015
DeepID3: Face Recognition with Very Deep Neural Networks Yi Sun Ding Liang Xiaogang Wang Xiaoou Tang CVBM 85 940 0 03 Feb 2015
Scalable Object Detection using Deep Neural Networks D. Erhan Christian Szegedy Alexander Toshev Dragomir Anguelov ObjD 112 1,165 0 08 Dec 2013
On the difficulty of training Recurrent Neural Networks Razvan Pascanu Tomas Mikolov Yoshua Bengio ODL 190 5,346 0 21 Nov 2012
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 353 7,942 0 13 Jun 2012

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