Fast Zero-Shot Image Tagging

31 May 2016

Papers citing "Fast Zero-Shot Image Tagging"

25 / 25 papers shown

Title
Nesterov Method for Asynchronous Pipeline Parallel Optimization Thalaiyasingam Ajanthan Sameera Ramasinghe Yan Zuo Gil Avraham Alexander Long 26 0 0 02 May 2025
Communication-Efficient Large-Scale Distributed Deep Learning: A Comprehensive Survey Feng Liang Zhen Zhang Haifeng Lu Victor C. M. Leung Yanyi Guo Xiping Hu GNN 37 6 0 09 Apr 2024
DropCompute: simple and more robust distributed synchronous training via compute variance reduction Niv Giladi Shahar Gottlieb Moran Shkolnik A. Karnieli Ron Banner Elad Hoffer Kfir Y. Levy Daniel Soudry 38 2 0 18 Jun 2023
PersA-FL: Personalized Asynchronous Federated Learning Taha Toghani Soomin Lee César A. Uribe FedML 52 6 0 03 Oct 2022
SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural Networks Chaoyang He Emir Ceyani Keshav Balasubramanian M. Annavaram Salman Avestimehr FedML 25 50 0 04 Jun 2021
A Runtime-Based Computational Performance Predictor for Deep Neural Network Training Geoffrey X. Yu Yubo Gao P. Golikov Gennady Pekhimenko 3DH 28 67 0 31 Jan 2021
Distributed Training of Deep Learning Models: A Taxonomic Perspective M. Langer Zhen He W. Rahayu Yanbo Xue 22 76 0 08 Jul 2020
FLeet: Online Federated Learning via Staleness Awareness and Performance Prediction Georgios Damaskinos R. Guerraoui Anne-Marie Kermarrec Vlad Nitu Rhicheek Patra Francois Taiani 13 54 0 12 Jun 2020
Pipelined Backpropagation at Scale: Training Large Models without Batches Atli Kosson Vitaliy Chiley Abhinav Venigalla Joel Hestness Urs Koster 35 33 0 25 Mar 2020
On the Convergence of Nesterov's Accelerated Gradient Method in Stochastic Settings Mahmoud Assran Michael G. Rabbat 14 59 0 27 Feb 2020
Asynchronous Federated Learning with Differential Privacy for Edge Intelligence Yanan Li Shusen Yang Xuebin Ren Cong Zhao FedML 19 33 0 17 Dec 2019
Demon: Improved Neural Network Training with Momentum Decay John Chen Cameron R. Wolfe Zhaoqi Li Anastasios Kyrillidis ODL 24 15 0 11 Oct 2019
Taming Momentum in a Distributed Asynchronous Environment Ido Hakimi Saar Barkai Moshe Gabel Assaf Schuster 19 23 0 26 Jul 2019
DEAM: Adaptive Momentum with Discriminative Weight for Stochastic Optimization Jiyang Bai Yuxiang Ren Jiawei Zhang ODL 21 1 0 25 Jul 2019
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
Quasi-hyperbolic momentum and Adam for deep learning Jerry Ma Denis Yarats ODL 84 129 0 16 Oct 2018
Toward Understanding the Impact of Staleness in Distributed Machine Learning Wei-Ming Dai Yi Zhou Nanqing Dong Huatian Zhang Eric Xing 22 80 0 08 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
Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance Benchmark Cody Coleman Daniel Kang Deepak Narayanan Luigi Nardi Tian Zhao Jian Zhang Peter Bailis K. Olukotun Christopher Ré Matei A. Zaharia 13 117 0 04 Jun 2018
Stochastic modified equations for the asynchronous stochastic gradient descent Jing An Jian-wei Lu Lexing Ying 21 79 0 21 May 2018
Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD Sanghamitra Dutta Gauri Joshi Soumyadip Ghosh Parijat Dube P. Nagpurkar 31 193 0 03 Mar 2018
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training Yujun Lin Song Han Huizi Mao Yu Wang W. Dally 44 1,386 0 05 Dec 2017
YellowFin and the Art of Momentum Tuning Jian Zhang Ioannis Mitliagkas ODL 23 108 0 12 Jun 2017
Asynchronous Stochastic Gradient Descent with Delay Compensation Shuxin Zheng Qi Meng Taifeng Wang Wei Chen Nenghai Yu Zhiming Ma Tie-Yan Liu 32 312 0 27 Sep 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