A Survey on Large-scale Machine Learning

10 August 2020

Meng Wang

Papers citing "A Survey on Large-scale Machine Learning"

21 / 21 papers shown

Title
Seamless Optical Cloud Computing across Edge-Metro Network for Generative AI Sizhe Xing Aolong Sun Chengxi Wang Yizhi Wang Boyu Dong ... Xi Xiao R. Penty Qixiang Cheng Nan Chi Junwen Zhang 126 0 0 04 Dec 2024
DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression Hanlin Tang Xiangru Lian Chen Yu Tong Zhang Ji Liu 21 217 0 15 May 2019
Towards Federated Learning at Scale: System Design Keith Bonawitz Hubert Eichner W. Grieskamp Dzmitry Huba A. Ingerman ... H. B. McMahan Timon Van Overveldt David Petrou Daniel Ramage Jason Roselander FedML 68 2,652 0 04 Feb 2019
Deformable ConvNets v2: More Deformable, Better Results Xizhou Zhu Han Hu Stephen Lin Jifeng Dai ObjD 64 1,998 0 27 Nov 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 162 5,024 0 19 Jun 2018
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training Chengyue Wu Song Han Huizi Mao Yu Wang W. Dally 91 1,394 0 05 Dec 2017
Don't Decay the Learning Rate, Increase the Batch Size Samuel L. Smith Pieter-Jan Kindermans Chris Ying Quoc V. Le ODL 71 990 0 01 Nov 2017
Theoretical insights into the optimization landscape of over-parameterized shallow neural networks Mahdi Soltanolkotabi Adel Javanmard Jason D. Lee 70 417 0 16 Jul 2017
A Survey on Learning to Hash Jingdong Wang Ting Zhang Jingkuan Song N. Sebe Heng Tao Shen 76 965 0 01 Jun 2016
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 223 18,300 0 27 May 2016
Communication-Efficient Distributed Dual Coordinate Ascent Martin Jaggi Virginia Smith Martin Takáč Jonathan Terhorst S. Krishnan Thomas Hofmann Michael I. Jordan 47 353 0 04 Sep 2014
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives Aaron Defazio Francis R. Bach Simon Lacoste-Julien ODL 76 1,817 0 01 Jul 2014
Caffe: Convolutional Architecture for Fast Feature Embedding Yangqing Jia Evan Shelhamer Jeff Donahue Sergey Karayev Jonathan Long Ross B. Girshick S. Guadarrama Trevor Darrell VLM BDL 3DV 127 14,703 0 20 Jun 2014
A Stochastic Quasi-Newton Method for Large-Scale Optimization R. Byrd Samantha Hansen J. Nocedal Y. Singer ODL 57 470 0 27 Jan 2014
Minimizing Finite Sums with the Stochastic Average Gradient Mark Schmidt Nicolas Le Roux Francis R. Bach 194 1,245 0 10 Sep 2013
A Survey on Multi-view Learning Chang Xu Dacheng Tao Chao Xu AI4TS 39 1,123 0 20 Apr 2013
Revisiting the Nystrom Method for Improved Large-Scale Machine Learning Alex Gittens Michael W. Mahoney 77 414 0 07 Mar 2013
ADADELTA: An Adaptive Learning Rate Method Matthew D. Zeiler ODL 67 6,619 0 22 Dec 2012
Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring S. Ahn Anoop Korattikara Balan Max Welling 35 305 0 27 Jun 2012
Representation Learning: A Review and New Perspectives Yoshua Bengio Aaron Courville Pascal Vincent OOD SSL 95 12,384 0 24 Jun 2012
Practical recommendations for gradient-based training of deep architectures Yoshua Bengio 3DH ODL 66 2,195 0 24 Jun 2012