30
/de/
AIzaSyAYiBZKx7MnpbEhh9jyipgxe19OcubqV5w
June 15, 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
Erstellen
Close
Create a timeline
Public timelines
Library
FAQ
8 März 2019 Jahr - ChengGong: $\mu$L2Q: An Ultra-Low Loss Quantization Method for DNN
Beschreibung:
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。
Zugefügt zum Band der Zeit:
Quantization timeline
By
龚成
29 Mär 2020
1
0
619
Datum:
8 März 2019 Jahr
Jetzt
~ 5 years and 2 months ago
About & Feedback
Vereinbarung
Privatheit
Bibliothek
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