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EdgeSync: Faster Edge-model Updating via Adaptive Continuous Learning
  for Video Data Drift

EdgeSync: Faster Edge-model Updating via Adaptive Continuous Learning for Video Data Drift

5 June 2024
Peng Zhao
Runchu Dong
Guiqin Wang
Cong Zhao
ArXivPDFHTML

Papers citing "EdgeSync: Faster Edge-model Updating via Adaptive Continuous Learning for Video Data Drift"

3 / 3 papers shown
Title
Improving GPU Multi-Tenancy Through Dynamic Multi-Instance GPU
  Reconfiguration
Improving GPU Multi-Tenancy Through Dynamic Multi-Instance GPU Reconfiguration
Tianyu Wang
Sheng R. Li
Bingyao Li
Yuezhen Dai
Ao Li
Geng Yuan
Yufei Ding
Youtao Zhang
Xulong Tang
32
0
0
18 Jul 2024
ELASTIC: Improving CNNs with Dynamic Scaling Policies
ELASTIC: Improving CNNs with Dynamic Scaling Policies
Huiyu Wang
Aniruddha Kembhavi
Ali Farhadi
Alan Yuille
Mohammad Rastegari
122
57
0
13 Dec 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
329
11,684
0
09 Mar 2017
1