"Approximate Computing for ML: State-of-the-art, Challenges and Visions."

Georgios Zervakis et al. (2021)

> Home

Details and statistics

DOI: 10.1145/3394885.3431632

access: closed

type: Conference or Workshop Paper

metadata version: 2022-04-06

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - conf/aspdac/ZervakisSAGPH21
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/aspdac/ZervakisSAGPH21
Georgios Zervakis, Hassaan Saadat, Hussam Amrouch, Andreas Gerstlauer, Sri Parameswaran, Jörg Henkel:
Approximate Computing for ML: State-of-the-art, Challenges and Visions. ASP-DAC 2021: 189-196

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.