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Results: 12
Number of items: 12
  • Arunachalam, S., Chakraborty, S., Koucký, M., Saurabh, N., & de Wolf, R. (2021). Improved Bounds on Fourier Entropy and Min-entropy. ACM Transactions on Computation Theory, 13(4), Article 22. https://doi.org/10.1145/3470860
  • Open Access
    Arunachalam, S., Chakraborty, S., Lee, T., Paraashar, M., & de Wolf, R. (2021). Two new results about quantum exact learning. Quantum, 5, Article 587. https://doi.org/10.22331/Q-2021-11-24-587, https://doi.org/10.48550/arXiv.1810.00481
  • Open Access
    Arunachalam, S., Vrana, P., & Zuiddam, J. (2020). The asymptotic induced matching number of hypergraphs: Balanced binary strings. Electronic Journal of Combinatorics, 27(3), Article P3.12. https://doi.org/10.37236/9019
  • Open Access
    Arunachalam, S., Belovs, A., Childs, A. M., Kothari, R., Rosmanis, A., & de Wolf, R. (2020). Quantum Coupon Collector. In S. T. Flammia (Ed.), 15th Conference on the Theory of Quantum Computation, Communication and Cryptography: TQC 2020, June 9-12, 2020, Riga, Latvia Article 10 (Leibniz International Proceedings in Informatics; Vol. 158). Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.TQC.2020.10
  • Open Access
    Arunachalam, S., Chakraborty, S., Koucký, M., Saurabh, N., & de Wolf, R. (2020). Improved bounds on Fourier entropy and Min-entropy. In C. Paul, & M. Bläser (Eds.), 37th International Symposium on Theoretical Aspects of Computer Science: STACS 2020, March 10-13, 2020, Montpellier, France Article 45 (Leibniz International Proceedings in Informatics; Vol. 154). Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.STACS.2020.45
  • Open Access
    Arunachalam, S., Chakraborty, S., Lee, T., Paraashar, M., & de Wolf, R. (2019). Two new results about quantum exact learning. In C. Baier, I. Chatzigiannakis, P. Flocchini, & S. Leonardi (Eds.), 46th International Colloquium on Automata, Languages, and Programming: ICALP 2019, July 9-12, 2019, Patras, Greece Article 16 (Leibniz International Proceedings in Informatics; Vol. 132). Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.ICALP.2019.16, https://doi.org/10.48550/arXiv.1810.00481
  • Open Access
    Arunachalam, S., & de Wolf, R. (2018). Optimal Quantum Sample Complexity of Learning Algorithms. Journal of Machine Learning Research, 19, Article 71. http://jmlr.org/papers/v19/18-195.html
  • Open Access
    Arunachalam, S. (2018). Quantum algorithms and learning theory. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Arunachalam, S., & de Wolf, R. (2017). Optimal quantum sample complexity of learning algorithms. In R. O'Donnell (Ed.), 32nd Computational Complexity Conference: CCC 2017, July 6-9, 2017, Riga, Latvia Article 25 (Leibniz International Proceedings in Informatics; Vol. 79). Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.CCC.2017.25
  • Open Access
    Gilyén, A., Arunachalam, S., & Wiebe, N. (2017). Optimizing quantum optimization algorithms via faster quantum gradient computation. (v2 ed.) ArXiv. https://arxiv.org/abs/1711.00465v2
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