30
/it/
AIzaSyAYiBZKx7MnpbEhh9jyipgxe19OcubqV5w
April 1, 2024
3251448
288434
1
Public Timelines
FAQ
Menu
Public Timelines
FAQ
Public Timelines
FAQ
For education
For educational institutions
For teachers
For students
Open cabinet
For educational institutions
For teachers
For students
Open cabinet
Creare
Close
Create a timeline
Public timelines
Library
FAQ
8 marzo 2019 anni - ChengGong: $\mu$L2Q: An Ultra-Low Loss Quantization Method for DNN
Descrizione:
本文实现了多位宽的量化方案。相比于二值三值或者定点数量化等方案,本文首次从权值分布角度进行量化,实现了多位宽的高精度量化。实验表明再相同条件下,uL2Q可以实现更低精度下降。
Aggiunto al nastro di tempo:
Quantization timeline
By
龚成
29 mar 2020
1
0
616
Data:
8 marzo 2019 anni
Adesso
~ 5 years and 2 months ago
About & Feedback
Accordo
Privatezza
Biblioteca
2024
©
Time.Graphics
Support 24/7
Cabinet
Get premium
Donate
The service accepts bank transfer (ACH, Wire) or cards (Visa, MasterCard, etc). Processed by Stripe.
Secured with SSL
Excellent (Trustpilot Reviews)
Based on 115+ reviews
Write your own review on
Trustpilot.com