• 40098 Citations
  • 57 h-Index
1987 …2019

Research output per year

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Fingerprint Dive into the research topics where Robert E. Schapire is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

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Projects

Research Output

Adversarial bandits with knapsacks

Immorlica, N., Sankararaman, K. A., Schapire, R. & Slivkins, A., Nov 2019, Proceedings - 2019 IEEE 60th Annual Symposium on Foundations of Computer Science, FOCS 2019. IEEE Computer Society, p. 202-219 18 p. 8948695. (Proceedings - Annual IEEE Symposium on Foundations of Computer Science, FOCS; vol. 2019-November).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Learning deep ResNet blocks sequentially using boosting theory

    Huang, F., Ash, J. T., Langford, J. & Schapire, R. E., Jan 1 2018, 35th International Conference on Machine Learning, ICML 2018. Dy, J. & Krause, A. (eds.). International Machine Learning Society (IMLS), p. 3272-3290 19 p. (35th International Conference on Machine Learning, ICML 2018; vol. 5).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • 3 Scopus citations

    On oracle-efficient PAC RL with rich observations

    Dann, C., Jiang, N., Krishnamurthy, A., Agarwal, A., Langford, J. & Schapire, R. E., Jan 1 2018, In : Advances in Neural Information Processing Systems. 2018-December, p. 1422-1432 11 p.

    Research output: Contribution to journalConference article

  • 2 Scopus citations

    Practical Contextual Bandits with Regression Oracles

    Foster, D. J., Agarwal, A., Dudik, M., Haipeng, L. & Schapire, R. E., Jan 1 2018, 35th International Conference on Machine Learning, ICML 2018. Dy, J. & Krause, A. (eds.). International Machine Learning Society (IMLS), p. 2482-2517 36 p. (35th International Conference on Machine Learning, ICML 2018; vol. 4).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • 3 Scopus citations

    Contextual decision processes with low Bellman rank are PAC-learnable

    Jiang, N., Krishnamurthy, A., Agarwal, A., Langford, J. & Schapire, R. E., Jan 1 2017, 34th International Conference on Machine Learning, ICML 2017. International Machine Learning Society (IMLS), p. 2671-2707 37 p. (34th International Conference on Machine Learning, ICML 2017; vol. 4).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • 9 Scopus citations