Matus Jan Telgarsky

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Research Output

  • 7 Conference contribution
  • 5 Conference article
  • 4 Article
  • 1 Paper

A gradual, semi-discrete approach to generative network training via explicit wasserstein minimization

Chen, Y., Telgarsky, M., Zhang, C., Bailey, B., Hsu, D. & Peng, J., 2019, 36th International Conference on Machine Learning, ICML 2019. International Machine Learning Society (IMLS), p. 1845-1858 14 p. (36th International Conference on Machine Learning, ICML 2019; vol. 2019-June).

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

  • Size-noise tradeoffs in generative networks

    Bailey, B. & Telgarsky, M., Jan 1 2018, In : Advances in Neural Information Processing Systems. 2018-December, p. 6489-6499 11 p.

    Research output: Contribution to journalConference article

  • Social welfare and profit maximization from revealed preferences

    Ji, Z., Mehta, R. & Telgarsky, M., Jan 1 2018, Web and Internet Economics - 14th International Conference, WINE 2018, Proceedings. Harks, T. & Christodoulou, G. (eds.). Springer-Verlag Berlin Heidelberg, p. 264-281 18 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11316 LNCS).

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

  • Neural networks and rational functions

    Telgarsky, M., 2017, 34th International Conference on Machine Learning, ICML 2017. International Machine Learning Society (IMLS), p. 5195-5210 16 p. (34th International Conference on Machine Learning, ICML 2017; vol. 7).

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

  • Spectrally-normalized margin bounds for neural networks

    Bartlett, P. L., Foster, D. J. & Telgarsky, M., Jan 1 2017, In : Advances in Neural Information Processing Systems. 2017-December, p. 6241-6250 10 p.

    Research output: Contribution to journalConference article