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Amit Daniely

Former affiliation
 https://orcid.org/0000-0002-3258-3509
    Calculated based on number of publications stored in Pure and citations from Scopus
    20112025

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    • 2023

      Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy

      Daniely, A., Srebro, N. & Vardi, G., 2023, Advances in Neural Information Processing Systems 36 - 37th Conference on Neural Information Processing Systems, NeurIPS 2023. Oh, A., Neumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Neural information processing systems foundation, (Advances in Neural Information Processing Systems; vol. 36).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

      1 Scopus citations

    • Most Neural Networks Are Almost Learnable

      Daniely, A., Srebro, N. & Vardi, G., 2023, Advances in Neural Information Processing Systems 36 - 37th Conference on Neural Information Processing Systems, NeurIPS 2023. Oh, A., Neumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Neural information processing systems foundation, (Advances in Neural Information Processing Systems; vol. 36).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

    • Multiclass Boosting: Simple and Intuitive Weak Learning Criteria

      Brukhim, N., Daniely, A., Mansour, Y. & Moran, S., 2023, Advances in Neural Information Processing Systems 36 - 37th Conference on Neural Information Processing Systems, NeurIPS 2023. Oh, A., Neumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Neural information processing systems foundation, (Advances in Neural Information Processing Systems; vol. 36).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

      3 Scopus citations
    • 2021

      Asynchronous Stochastic Optimization Robust to Arbitrary Delays

      Cohen, A., Daniely, A., Drori, Y., Koren, T. & Schain, M., 2021, Advances in Neural Information Processing Systems 34 - 35th Conference on Neural Information Processing Systems, NeurIPS 2021. Ranzato, M., Beygelzimer, A., Dauphin, Y., Liang, P. S. & Wortman Vaughan, J. (eds.). Neural information processing systems foundation, p. 9024-9035 12 p. (Advances in Neural Information Processing Systems; vol. 11).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

      20 Scopus citations
    • 2017

      Depth Separation for Neural Networks.

      Daniely, A., 2017, COLT 2017. PMLR, p. 690-696 7 p. (Proceedings of Machine Learning Research; vol. 65).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

    • 2016

      Complexity theoretic limitations on learning halfspaces

      Daniely, A., 19 Jun 2016, STOC 2016 - Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing. Mansour, Y. & Wichs, D. (eds.). Association for Computing Machinery, p. 105-117 13 p. (Proceedings of the Annual ACM Symposium on Theory of Computing; vol. 19-21-June-2016).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

      Open Access
      84 Scopus citations
    • 2015

      Inapproximability of truthful mechanisms via generalizations of the VC dimension

      Daniely, A., Schapira, M. & Shahaf, G., 14 Jun 2015, STOC 2015 - Proceedings of the 2015 ACM Symposium on Theory of Computing. Association for Computing Machinery, p. 401-408 8 p. (Proceedings of the Annual ACM Symposium on Theory of Computing; vol. 14-17-June-2015).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

      Open Access
      25 Scopus citations

    • Strongly adaptive online learning

      Daniely, A., Gonen, A. & Shalev-Shwartz, S., 2015, 32nd International Conference on Machine Learning, ICML 2015. Blei, D. & Bach, F. (eds.). International Machine Learning Society (IMLS), p. 1405-1411 7 p. (32nd International Conference on Machine Learning, ICML 2015; vol. 2).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

      131 Scopus citations
    • 2014

      From average case complexity to improper learning complexity

      Daniely, A., Linial, N. & Shalev-Shwartz, S., 2014, STOC 2014 - Proceedings of the 2014 ACM Symposium on Theory of Computing. Association for Computing Machinery, p. 441-448 8 p. (Proceedings of the Annual ACM Symposium on Theory of Computing).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

      Open Access
      70 Scopus citations
    • 2013

      On the practically interesting instances of MAXCUT

      Bilu, Y., Daniely, A., Linial, N. & Saks, M., 2013, 30th International Symposium on Theoretical Aspects of Computer Science, STACS 2013. p. 526-537 12 p. (Leibniz International Proceedings in Informatics, LIPIcs; vol. 20).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

      17 Scopus citations
    • 2012

      Multiclass learning approaches: A theoretical comparison with implications

      Daniely, A., Sabato, S. & Shalev-Shwartz, S., 2012, Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012, NIPS 2012. p. 485-493 9 p. (Advances in Neural Information Processing Systems; vol. 1).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

      23 Scopus citations
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