Quantizing data for distributed learning

14 December 2020

Suhas Diggavi

Papers citing "Quantizing data for distributed learning"

24 / 24 papers shown

Title
Influence Functions in Deep Learning Are Fragile S. Basu Phillip E. Pope Soheil Feizi TDI 77 226 0 25 Jun 2020
SQuARM-SGD: Communication-Efficient Momentum SGD for Decentralized Optimization Navjot Singh Deepesh Data Jemin George Suhas Diggavi 23 55 0 13 May 2020
RATQ: A Universal Fixed-Length Quantizer for Stochastic Optimization Prathamesh Mayekar Himanshu Tyagi MQ 48 48 0 22 Aug 2019
Fixing the train-test resolution discrepancy Hugo Touvron Andrea Vedaldi Matthijs Douze Hervé Jégou 102 423 0 14 Jun 2019
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification, and Local Computations Debraj Basu Deepesh Data C. Karakuş Suhas Diggavi MQ 38 403 0 06 Jun 2019
Efficient Augmentation via Data Subsampling Michael Kuchnik Virginia Smith 82 22 0 11 Oct 2018
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 951 93,936 0 11 Oct 2018
The Convergence of Sparsified Gradient Methods Dan Alistarh Torsten Hoefler M. Johansson Sarit Khirirat Nikola Konstantinov Cédric Renggli 114 491 0 27 Sep 2018
Sparsified SGD with Memory Sebastian U. Stich Jean-Baptiste Cordonnier Martin Jaggi 66 743 0 20 Sep 2018
Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization Jiaxiang Wu Weidong Huang Junzhou Huang Tong Zhang 59 235 0 21 Jun 2018
cpSGD: Communication-efficient and differentially-private distributed SGD Naman Agarwal A. Suresh Felix X. Yu Sanjiv Kumar H. B. McMahan FedML 111 490 0 27 May 2018
signSGD: Compressed Optimisation for Non-Convex Problems Jeremy Bernstein Yu Wang Kamyar Azizzadenesheli Anima Anandkumar FedML ODL 78 1,026 0 13 Feb 2018
Regularized Evolution for Image Classifier Architecture Search Esteban Real A. Aggarwal Yanping Huang Quoc V. Le 125 3,021 0 05 Feb 2018
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training Chengyue Wu Song Han Huizi Mao Yu Wang W. Dally 102 1,399 0 05 Dec 2017
TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning W. Wen Cong Xu Feng Yan Chunpeng Wu Yandan Wang Yiran Chen Hai Helen Li 123 985 0 22 May 2017
Sparse Communication for Distributed Gradient Descent Alham Fikri Aji Kenneth Heafield 56 738 0 17 Apr 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 136 2,854 0 14 Mar 2017
Distributed Mean Estimation with Limited Communication A. Suresh Felix X. Yu Sanjiv Kumar H. B. McMahan FedML 93 362 0 02 Nov 2016
QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding Dan Alistarh Demjan Grubic Jerry Li Ryota Tomioka Milan Vojnović MQ 53 425 0 07 Oct 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 1.4K 192,638 0 10 Dec 2015
Taming the Wild: A Unified Analysis of Hogwild!-Style Algorithms Christopher De Sa Ce Zhang K. Olukotun Christopher Ré 52 204 0 22 Jun 2015
Stochastic Optimization with Importance Sampling P. Zhao Tong Zhang 63 343 0 13 Jan 2014
Stochastic First- and Zeroth-order Methods for Nonconvex Stochastic Programming Saeed Ghadimi Guanghui Lan ODL 71 1,538 0 22 Sep 2013
Information-theoretic lower bounds on the oracle complexity of stochastic convex optimization Alekh Agarwal Peter L. Bartlett Pradeep Ravikumar Martin J. Wainwright 118 248 0 03 Sep 2010