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Low-rank Gradient Approximation For Memory-Efficient On-device Training
  of Deep Neural Network

Low-rank Gradient Approximation For Memory-Efficient On-device Training of Deep Neural Network

24 January 2020
Mary Gooneratne
K. Sim
P. Zadrazil
Andreas Kabel
F. Beaufays
Giovanni Motta
ArXiv (abs)PDFHTML

Papers citing "Low-rank Gradient Approximation For Memory-Efficient On-device Training of Deep Neural Network"

12 / 12 papers shown
Title
AdaRankGrad: Adaptive Gradient-Rank and Moments for Memory-Efficient LLMs Training and Fine-Tuning
AdaRankGrad: Adaptive Gradient-Rank and Moments for Memory-Efficient LLMs Training and Fine-Tuning
Yehonathan Refael
Jonathan Svirsky
Boris Shustin
Wasim Huleihel
Ofir Lindenbaum
91
4
0
31 Dec 2024
Personalization of End-to-end Speech Recognition On Mobile Devices For
  Named Entities
Personalization of End-to-end Speech Recognition On Mobile Devices For Named Entities
K. Sim
F. Beaufays
Arnaud Benard
Dhruv Guliani
Andreas Kabel
...
P. Zadrazil
Harry Zhang
Leif T. Johnson
Giovanni Motta
Lillian Zhou
65
83
0
14 Dec 2019
An Investigation Into On-device Personalization of End-to-end Automatic
  Speech Recognition Models
An Investigation Into On-device Personalization of End-to-end Automatic Speech Recognition Models
K. Sim
P. Zadrazil
F. Beaufays
76
58
0
14 Sep 2019
Streaming End-to-end Speech Recognition For Mobile Devices
Streaming End-to-end Speech Recognition For Mobile Devices
Yanzhang He
Tara N. Sainath
Rohit Prabhavalkar
Ian McGraw
R. Álvarez
...
K. Sim
Tom Bagby
Shuo-yiin Chang
Kanishka Rao
A. Gruenstein
114
627
0
15 Nov 2018
Apprentice: Using Knowledge Distillation Techniques To Improve
  Low-Precision Network Accuracy
Apprentice: Using Knowledge Distillation Techniques To Improve Low-Precision Network Accuracy
Asit K. Mishra
Debbie Marr
FedML
65
331
0
15 Nov 2017
Knowledge Distillation for Small-footprint Highway Networks
Knowledge Distillation for Small-footprint Highway Networks
Liang Lu
Michelle Guo
Steve Renals
65
73
0
02 Aug 2016
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed
  Systems
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Martín Abadi
Ashish Agarwal
P. Barham
E. Brevdo
Zhiwen Chen
...
Pete Warden
Martin Wattenberg
Martin Wicke
Yuan Yu
Xiaoqiang Zheng
282
11,150
0
14 Mar 2016
Deep Learning with Limited Numerical Precision
Deep Learning with Limited Numerical Precision
Suyog Gupta
A. Agrawal
K. Gopalakrishnan
P. Narayanan
HAI
207
2,049
0
09 Feb 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
2.0K
150,312
0
22 Dec 2014
GPU Asynchronous Stochastic Gradient Descent to Speed Up Neural Network
  Training
GPU Asynchronous Stochastic Gradient Descent to Speed Up Neural Network Training
T. Paine
Hailin Jin
Jianchao Yang
Zhe Lin
Thomas Huang
108
98
0
21 Dec 2013
Multi-GPU Training of ConvNets
Multi-GPU Training of ConvNets
Guillermo A. Castillo
Keith Adams
Yaniv Taigman
Ayonga Hereid
67
101
0
20 Dec 2013
Sequence Transduction with Recurrent Neural Networks
Sequence Transduction with Recurrent Neural Networks
Alex Graves
193
1,871
0
14 Nov 2012
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