Olivier Bousquet
Bousquet and André Elisseeff published Stability and Generalization in JMLR. They linked stability of learning algorithms with bounds on unseen-data error and studied regularized methods, including support-vector machines. Bousquet, Yegor Klochkov and Nikita Zhivotovskiy developed sharper bounds for uniformly stable algorithms. The paper was submitted in 2019 and revised in 2020. Bousquet coauthored Proper Learning, Helly Number, and an Optimal SVM Bound. The study relates a geometric-combinatorial parameter to learning sample complexity and gives a bound for SVMs in the realizable setting.
- Works
- 168
- Citations
- 18,246
- h-index
- 48
Publication numbers from OpenAlex, as of 14 October 2026.
Timeline
-
2002
Stability and generalization
Bousquet and André Elisseeff published Stability and Generalization in JMLR. They linked stability of learning algorithms with bounds on unseen-data error and studied regularized methods, including support-vector machines.
-
2019–2020
Sharper stability bounds
Bousquet, Yegor Klochkov and Nikita Zhivotovskiy developed sharper bounds for uniformly stable algorithms. The paper was submitted in 2019 and revised in 2020.
-
2020
Proper learning and SVM bounds
Bousquet coauthored Proper Learning, Helly Number, and an Optimal SVM Bound. The study relates a geometric-combinatorial parameter to learning sample complexity and gives a bound for SVMs in the realizable setting.
Sources and credits
Photo: ellis.eu; Olivier Bousquet | European Laboratory for Learning and Intelligent Systems; creator not stated. License: Not stated by source. Source: ellis.eu. Cropped to a square and resized. Ask us to remove or replace this photo.