Yoav S. Freund
Yoav S. Freund’s workshop archive preserves the talks and papers of the July 1999 DIMACS meeting on online decision algorithms at Rutgers, which concerned sequential decisions. At that time he was at AT&T Labs-Research. Freund coauthored Generalization Bounds for Averaged Classifiers with Yishay Mansour and Robert Schapire. The paper analyzes a binary classification method and its generalization behavior, linking prediction combinations with learning theory. Freund’s work at UC San Diego centers on computational learning theory and includes JBoost, a Java implementation of AdaBoost and related boosting algorithms. He also teaches online learning and statistical learning.
- Works
- 211
- Citations
- 52,263
- h-index
- 48
Publication numbers from OpenAlex, as of 14 October 2026.
Timeline
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1999
Online decision research
The July 1999 DIMACS meeting at Rutgers focused on online decision algorithms and sequential decisions. At that time he was at AT&T Labs-Research.
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2004 journal paper
Averaged classifiers
Freund coauthored Generalization Bounds for Averaged Classifiers with Yishay Mansour and Robert Schapire. The paper analyzes a binary classification method and its generalization behavior, linking prediction combinations with learning theory.
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Research and software
Boosting tools
Freund’s work at UC San Diego centers on computational learning theory and includes JBoost, a Java implementation of AdaBoost and related boosting algorithms. He also teaches online learning and statistical learning.
Sources and credits
Photo: Yoav Freund, via Wikimedia Commons. License: CC BY 3.0. Source: commons.wikimedia.org. Cropped to a square and resized. Ask us to remove or replace this photo.
