Exploring Communication Efficient Parallel Split Learning

Exploring Communication Efficient Parallel Split Learning reveals several interesting facts.

  • Recorded talk [best effort]. Speaker: Torsten Hoefler Conference: DFN Webinar Abstract: Deep Neural Networks (DNNs) are ...
  • Abstract: Federated learning (FL) is a popular distributed privacy-preserving machine learning (DPML) approach.
  • Yusuke Koda, Jihong Park, Mehdi Bennis, Koji Yamamoto, Takayuki Nishio, Masahiro Morikura (Kyoto Univ, Deakin Univ, Univ. of ...
  • Ali Abedi and Sheroz S. Khan (KITE, University Health Network, Canada. University of Toronto Canada.) @Workshop on
  • Workshop on

In-Depth Information on Communication Efficient Parallel Split Learning

Jihong Park, Seungeun Oh, Hyelin Nam, Seong-Lyun Kim, Mehdi Bennis (Deakin University, Yonsei University, University of ... I will present our recent work on Friction in data sharing and restrictive resource constraints pose to be a great challenge for large scale machine This is a recording of my presentation on our paper "

A complete training run in DLaaS with

Stay tuned for more updates related to Communication Efficient Parallel Split Learning.

Communication Efficient Parallel Split Learning.pdf

Size: 14.62 MB · Format: PDF · Secure Download

Download PDF Read Online

Related Documents