Publication / RESOURCE PROFILE

GACT: Activation Compressed Training for Generic Network Architectures

GACT: Activation Compressed Training for Generic Network ArchitecturesXiaoxuan Liu, Lianmin Zheng, Dequan Wang, Yukuo Cen, Weize Chen,&nb...

proceedings.mlr.pressPublished Jun 28, 2022
Visit source website ↗

Overview

GACT: Activation Compressed Training for Generic Network ArchitecturesXiaoxuan Liu, Lianmin Zheng, Dequan Wang, Yukuo Cen, Weize Chen,&nb...

Publication information

Publication title
GACT: Activation Compressed Training for Generic Network Architectures
Authors
Xiaoxuan Liu, Lianmin Zheng, Dequan Wang, Yukuo Cen, Weize Chen, Xu Han, Jianfei Chen, Zhiyuan Liu, Jie Tang, Joey Gonzalez, Michael Mahoney, Alvin Cheung
Published
Jun 28, 2022
Venue / journal
International Conference on Machine Learning
Publication source
proceedings.mlr.press · v162/liu22v.html ↗
PDF
Read the publisher PDF ↗

Source: Publisher citation HTML metadata · observed Oct 11, 2026.

Publisher page information

Source page title
GACT: Activation Compressed Training for Generic Network Architectures
Site name (reported)
PMLR
Declared page language
en
Observed source URL
https://proceedings.mlr.press/v162/liu22v.html ↗
Publisher canonical URL
https://proceedings.mlr.press/v162/liu22v.html ↗
Source metadata observed
Oct 11, 2026

Recorded from the source page’s published HTML metadata. Publisher page language can differ from this directory’s English interface.

Source links & provenance

https://proceedings.mlr.press/v162/liu22v.html ↗

Discovery references

References explain how this resource entered the collection. They do not represent an endorsement.

Explore related resources

Screenshot unavailableResource information and source links remain available. DeepIntoStreams/TSFM_Finance — reviewed source website screenshot
RepositoryChecked capture

DeepIntoStreams/TSFM_Finance

github.com

the official implementation of the paper “Re(visiting) Time Series Foundation Models in Finance”.

GitHub stars
31
Language
Jupyter Notebook
Code license
Apache-2.0
foundation-modeltime-seriesresearch-lab
96 Authority 96 / 100 Cited by 2 resources in this directory 2 discovery sources Directory record updated: 2026-10-11 How scoring works →

Sign In

Register

Reset Password

Please enter your username or email address, you will receive a link to create a new password via email.