SparkNet: Training Deep Networks in Spark

19 November 2015

Papers citing "SparkNet: Training Deep Networks in Spark"

28 / 28 papers shown

Title
Correlated Quantization for Faster Nonconvex Distributed Optimization Andrei Panferov Yury Demidovich Ahmad Rammal Peter Richtárik MQ 47 4 0 10 Jan 2024
Robust and Privacy-Preserving Collaborative Learning: A Comprehensive Survey Shangwei Guo Xu Zhang Feiyu Yang Tianwei Zhang Yan Gan Tao Xiang Yang Liu FedML 31 9 0 19 Dec 2021
BAGUA: Scaling up Distributed Learning with System Relaxations Shaoduo Gan Xiangru Lian Rui Wang Jianbin Chang Chengjun Liu ... Jiawei Jiang Binhang Yuan Sen Yang Ji Liu Ce Zhang 25 30 0 03 Jul 2021
SAPAG: A Self-Adaptive Privacy Attack From Gradients Yijue Wang Jieren Deng Danyi Guo Chenghong Wang Xianrui Meng Hang Liu Caiwen Ding Sanguthevar Rajasekaran 12 35 0 14 Sep 2020
Distributed Training of Deep Learning Models: A Taxonomic Perspective M. Langer Zhen He W. Rahayu Yanbo Xue 27 76 0 08 Jul 2020
An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies David Enthoven Zaid Al-Ars FedML 60 50 0 01 Apr 2020
Convergence of Edge Computing and Deep Learning: A Comprehensive Survey Xiaofei Wang Yiwen Han Victor C. M. Leung Dusit Niyato Xueqiang Yan Xu Chen 17 977 0 19 Jul 2019
Bayesian Nonparametric Federated Learning of Neural Networks Mikhail Yurochkin Mayank Agarwal S. Ghosh Kristjan Greenewald T. Hoang Y. Khazaeni FedML 12 720 0 28 May 2019
TF-Replicator: Distributed Machine Learning for Researchers P. Buchlovsky David Budden Dominik Grewe Chris Jones John Aslanides ... Aidan Clark Sergio Gomez Colmenarejo Aedan Pope Fabio Viola Dan Belov GNN OffRL AI4CE 37 20 0 01 Feb 2019
Pipe-SGD: A Decentralized Pipelined SGD Framework for Distributed Deep Net Training Youjie Li Hang Qiu Songze Li A. Avestimehr N. Kim A. Schwing FedML 18 104 0 08 Nov 2018
Adaptive Communication Strategies to Achieve the Best Error-Runtime Trade-off in Local-Update SGD Jianyu Wang Gauri Joshi FedML 33 231 0 19 Oct 2018
Characterizing Deep-Learning I/O Workloads in TensorFlow Steven W. D. Chien Stefano Markidis C. Sishtla Luís Santos Pawel Herman Sai B. Narasimhamurthy Erwin Laure 21 50 0 06 Oct 2018
Cooperative SGD: A unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms Jianyu Wang Gauri Joshi 33 348 0 22 Aug 2018
Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication Felix Sattler Simon Wiedemann K. Müller Wojciech Samek MQ 36 211 0 22 May 2018
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 78 1,455 0 10 May 2018
Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis Tal Ben-Nun Torsten Hoefler GNN 33 703 0 26 Feb 2018
SLAQ: Quality-Driven Scheduling for Distributed Machine Learning Haoyu Zhang Logan Stafman Andrew Or M. Freedman 38 140 0 13 Feb 2018
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training Yujun Lin Song Han Huizi Mao Yu Wang W. Dally 44 1,388 0 05 Dec 2017
What does fault tolerant Deep Learning need from MPI? Vinay C. Amatya Abhinav Vishnu Charles Siegel J. Daily 28 19 0 11 Sep 2017
Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters Huatian Zhang Zeyu Zheng Shizhen Xu Wei-Ming Dai Qirong Ho Xiaodan Liang Zhiting Hu Jinliang Wei P. Xie Eric Xing GNN 33 343 0 11 Jun 2017
Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent Yudong Chen Lili Su Jiaming Xu FedML 19 241 0 16 May 2017
Deep Learning in the Automotive Industry: Applications and Tools André Luckow M. Cook Nathan Ashcraft Edwin Weill Emil Djerekarov Bennie Vorster 17 116 0 30 Apr 2017
Exploring the Design Space of Deep Convolutional Neural Networks at Large Scale F. Iandola 3DV 26 18 0 20 Dec 2016
Omnivore: An Optimizer for Multi-device Deep Learning on CPUs and GPUs Stefan Hadjis Ce Zhang Ioannis Mitliagkas Dan Iter Christopher Ré 20 65 0 14 Jun 2016
TensorFlow: A system for large-scale machine learning Martín Abadi P. Barham Jianmin Chen Z. Chen Andy Davis ... Vijay Vasudevan Pete Warden Martin Wicke Yuan Yu Xiaoqiang Zhang GNN AI4CE 101 18,262 0 27 May 2016
Computing Web-scale Topic Models using an Asynchronous Parameter Server R. Jagerman Carsten Eickhoff Maarten de Rijke 18 15 0 24 May 2016
DeepSpark: A Spark-Based Distributed Deep Learning Framework for Commodity Clusters Hanjoo Kim Jaehong Park Jaehee Jang Sungroh Yoon BDL 32 37 0 26 Feb 2016
Strategies and Principles of Distributed Machine Learning on Big Data Eric Xing Qirong Ho P. Xie Wei-Ming Dai AI4CE 24 153 0 31 Dec 2015