Yoram Singer
Singer worked at AT&T from 1995 to 1999 and was an associate professor at the Hebrew University from 1999 to 2007. His later career included Google research and a Princeton professorship. Singer coauthored Adaptive Subgradient Methods for Online Learning and Stochastic Optimization with John Duchi and Elad Hazan. The paper uses geometry from earlier observations to adapt gradient-based learning and provides formal regret guarantees under assumptions. Singer co-founded Sibyl, used for multiple YouTube prediction tasks during 2008–2018. He also worked on Google’s domain-spam classifier and research programs in effective machine learning.
- Works
- 214
- Citations
- 41,612
- h-index
- 62
Publication numbers from OpenAlex, as of 14 October 2026.
Timeline
-
1995–2007
Research and university work
Singer worked at AT&T from 1995 to 1999 and was an associate professor at the Hebrew University from 1999 to 2007. His later career included Google research and a Princeton professorship.
-
2011
Adaptive learning steps
Singer coauthored Adaptive Subgradient Methods for Online Learning and Stochastic Optimization with John Duchi and Elad Hazan. The paper uses geometry from earlier observations to adapt gradient-based learning and provides formal regret guarantees under assumptions.
-
2008–2018
Learning infrastructure
Singer co-founded Sibyl, used for multiple YouTube prediction tasks during 2008–2018. He also worked on Google’s domain-spam classifier and research programs in effective machine learning.
Sources and credits
Photo: cs.princeton.edu; Singer, Russakovsky, Lloyd Join Computer Science Faculty | CS; creator not stated. License: Not stated by source. Source: cs.princeton.edu. Cropped to a square and resized. Ask us to remove or replace this photo.