Conquering the Communication Constraints to Enable Large Pre-Trained Models in Federated Learning

4 October 2022

Papers citing "Conquering the Communication Constraints to Enable Large Pre-Trained Models in Federated Learning"

7 / 7 papers shown

Title
AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition Shoufa Chen Chongjian Ge Zhan Tong Jiangliu Wang Yibing Song Jue Wang Ping Luo 111 373 0 26 May 2022
P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks Xiao Liu Kaixuan Ji Yicheng Fu Weng Lam Tam Zhengxiao Du Zhilin Yang Jie Tang VLM 203 604 0 14 Oct 2021
CPT: Colorful Prompt Tuning for Pre-trained Vision-Language Models Yuan Yao Ao Zhang Zhengyan Zhang Zhiyuan Liu Tat-Seng Chua Maosong Sun MLLM VPVLM VLM 150 178 0 24 Sep 2021
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 255 4,299 0 29 Apr 2021
ImageNet-21K Pretraining for the Masses T. Ridnik Emanuel Ben-Baruch Asaf Noy Lihi Zelnik-Manor SSeg VLM CLIP 138 542 0 22 Apr 2021
Is Space-Time Attention All You Need for Video Understanding? Gedas Bertasius Heng Wang Lorenzo Torresani ViT 253 1,486 0 09 Feb 2021
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 249 9,997 0 01 Sep 2014