ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1905.01416
  4. Cited By
SinReQ: Generalized Sinusoidal Regularization for Low-Bitwidth Deep
  Quantized Training

SinReQ: Generalized Sinusoidal Regularization for Low-Bitwidth Deep Quantized Training

4 May 2019
Ahmed T. Elthakeb
Prannoy Pilligundla
H. Esmaeilzadeh
    MQ
ArXivPDFHTML

Papers citing "SinReQ: Generalized Sinusoidal Regularization for Low-Bitwidth Deep Quantized Training"

4 / 4 papers shown
Title
Quantization-Guided Training for Compact TinyML Models
Quantization-Guided Training for Compact TinyML Models
Sedigh Ghamari
Koray Ozcan
Thu Dinh
A. Melnikov
Juan Carvajal
Jan Ernst
S. Chai
MQ
16
16
0
10 Mar 2021
ReLeQ: A Reinforcement Learning Approach for Deep Quantization of Neural
  Networks
ReLeQ: A Reinforcement Learning Approach for Deep Quantization of Neural Networks
Ahmed T. Elthakeb
Prannoy Pilligundla
Fatemehsadat Mireshghallah
Amir Yazdanbakhsh
H. Esmaeilzadeh
MQ
55
68
0
05 Nov 2018
Incremental Network Quantization: Towards Lossless CNNs with
  Low-Precision Weights
Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights
Aojun Zhou
Anbang Yao
Yiwen Guo
Lin Xu
Yurong Chen
MQ
331
1,049
0
10 Feb 2017
The Loss Surfaces of Multilayer Networks
The Loss Surfaces of Multilayer Networks
A. Choromańska
Mikael Henaff
Michaël Mathieu
Gerard Ben Arous
Yann LeCun
ODL
179
1,185
0
30 Nov 2014
1