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  • 2022

    Learning with metric losses.

    Cohen, D. T. & Kontorovich, A., 2022, COLT. p. 662-700 39 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

  • 2021

    Dimension-Free Empirical Entropy Estimation

    Cohen, D., Kontorovich, A., Koolyk, A. & Wolfer, G., 1 Jan 2021, Advances in Neural Information Processing Systems 34 - 35th Conference on Neural Information Processing Systems, NeurIPS 2021. Ranzato, MA., Beygelzimer, A., Dauphin, Y., Liang, P. S. & Wortman Vaughan, J. (eds.). Neural information processing systems foundation, p. 13911-13923 13 p. (Advances in Neural Information Processing Systems; vol. 17).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    1 Scopus citations
  • Dimension-free empirical entropy estimation.

    Cohen, D., Kontorovich, A., Koolyk, A. & Wolfer, G., 2021, Advances in Neural Information Processing Systems 34 (NeurIPS 2021). p. 13911-13923 13 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

  • Nested Barycentric Coordinate System as an Explicit Feature Map

    Gottlieb, L-A., Kaufman, E., Kontorovich, A., Nivasch, G. & Pele, O., 2021, Proceedings of The 24th International Conference on Artificial Intelligence and Statistics. Banerjee, A. & Fukumizu, K. (eds.). PMLR, Vol. 130. p. 766-774 9 p. (Proceedings of Machine Learning Research).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

  • Stable Sample Compression Schemes: New Applications and an Optimal SVM Margin Bound

    Hanneke, S. & Kontorovich, A., 2021, Algorithmic Learning Theory. p. 697-721 25 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

  • 2020

    Algorithmic Learning Theory 2020: Preface

    Kontorovich, A. & Neu, G., 1 Aug 2020, Proceedings of the 31st International Conference on Algorithmic Learning Theory. Kontorovich, A. & Neu, G. (eds.). San Diego, California, USA: PMLR, Vol. 117. p. 1-2 2 p. (Proceedings of Machine Learning Research).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

  • Fast and Bayes-Consistent Nearest neighbors

    Efremenko, K., Kontorovich, A. & Noivirt, M., 2020, The 23rd International Conference on Artificial Intelligence and Statistics, AISTATS 2020, 26-28 August 2020, Online [Palermo, Sicily, Italy]. Chiappa, S. & Calandra, R. (eds.). PMLR, Vol. 108. p. 1276-1286 11 p. (Proceedings of Machine Learning Research).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

  • Minimax Testing of Identity to a Reference Ergodic Markov Chain

    Wolfer, G. & Kontorovich, A., 2020, Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics. Chiappa, S. & Calandra, R. (eds.). PMLR, Vol. 108. p. 191-201 11 p. (Proceedings of Machine Learning Research).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

  • Universal Bayes Consistency in Metric Spaces

    Hanneke, S., Kontorovich, A., Sabato, S. & Weiss, R., 2 Feb 2020, 2020 Information Theory and Applications Workshop, ITA 2020. Institute of Electrical and Electronics Engineers Inc., 9244988

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

  • 2019

    A Sharp Lower Bound for Agnostic Learning with Sample Compression Schemes

    Hanneke, S. & Kontorovich, A., 1 Oct 2019, Proceedings of the 30th International Conference on Algorithmic Learning Theory. Garivier, A. & Kale, S. (eds.). Chicago, Illinois: PMLR, Vol. 98. p. 489-505 17 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

  • Estimating the Mixing Time of Ergodic Markov Chains

    Wolfer, G. & Kontorovich, A., 1 Jun 2019, Proceedings of Machine Learning Research: Conference on Learning Theory, 25-28 June 2019, Phoenix, USA. Vol. 99. 1 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

  • Improved Generalization Bounds for Robust Learning

    Attias, I., Kontorovich, A. & Mansour, Y., 2019, Algorithmic Learning Theory, ALT 2019, 22-24 March 2019, Chicago, Illinois, USA. Garivier, A. & Kale, S. (eds.). PMLR, Vol. 98. p. 162-183 22 p. (Proceedings of Machine Learning Research).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

  • Minimax Learning of Ergodic Markov Chains

    Wolfer, G. & Kontorovich, A., 2019, Proceedings of Machine Learning Research. Vol. 98. p. 1-27

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

  • Sample Compression for Real-Valued Learners

    Hanneke, S., Kontorovich, A. & Sadigurschi, M., 2019, Proceedings of the 30th International Conference on Algorithmic Learning Theory. Garivier, A. & Kale, S. (eds.). Chicago, Illinois: PMLR, Vol. 98. p. 466-488 23 p. (Proceedings of Machine Learning Research).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

  • Temporal anomaly detection: Calibrating the surprise

    Gutflaish, E., Kontorovich, A., Sabato, S., Biller, O. & Sofer, O., 1 Jan 2019, 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019. AAAI press, p. 3755-3762 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    1 Scopus citations
  • 2018

    Advanced Analytics for Connected Car Cybersecurity

    Levi, M., Allouche, Y. & Kontorovich, A., 20 Jul 2018, 2018 IEEE 87th Vehicular Technology Conference, VTC Spring 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., Vol. 2018-June. p. 1-7 7 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    25 Scopus citations
  • 2017

    Concentration of Measure Without Independence: A Unified Approach Via the Martingale Method

    Kontorovich, A. & Raginsky, M., 2017, Convexity and Concentration. Carlen, E., Madiman, M. & Werner, E. M. (eds.). New York, NY: Springer New York, p. 183-210 28 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

  • Nearest-Neighbor sample compression: Efficiency, consistency, infinite dimensions

    Kontorovich, A., Sabato, S. & Weiss, R., 1 Jan 2017, Advances in Neural Information Processing Systems. Vol. 2017. p. 1574-1584 11 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    9 Scopus citations
  • 2016

    Active nearest-neighbor learning in metric spaces

    Kontorovich, A., Sabato, S. & Urner, R., 1 Jan 2016, Advances in Neural Information Processing Systems. p. 856-864 9 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    9 Scopus citations
  • 2014

    Concentration in unbounded metric spaces and algorithmic stability

    Kontorovich, A., 1 Jan 2014, 31st International Conference on Machine Learning, ICML 2014. International Machine Learning Society (IMLS), Vol. 2. p. 1185-1195 11 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    7 Scopus citations
  • Maximum margin multiclass nearest neighbors

    Kontorovich, A. & Weiss, R., 1 Jan 2014, 31st International Conference on Machine Learning, ICML 2014. International Machine Learning Society (IMLS), p. 2501-2511 11 p. (31st International Conference on Machine Learning, ICML 2014; vol. 3).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    17 Scopus citations
  • 2013

    Adaptive metric dimensionality reduction

    Gottlieb, L. A., Kontorovich, A. & Krauthgamer, R., 18 Nov 2013, Algorithmic Learning Theory - 24th International Conference, ALT 2013, Proceedings. p. 279-293 15 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 8139 LNAI).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

  • Efficient determination of the unique decodability of a string

    Filtser, A., Jin, J., Kontorovich, A. & Trachtenberg, A., 19 Dec 2013, 2013 IEEE International Symposium on Information Theory, ISIT 2013. p. 1411-1415 5 p. 6620459. (IEEE International Symposium on Information Theory - Proceedings).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    1 Scopus citations
  • Efficient regression in metric spaces via approximate Lipschitz extension

    Gottlieb, L. A., Kontorovich, A. & Krauthgamer, R., 12 Jul 2013, Similarity-Based Pattern Recognition - Second International Workshop, SIMBAD 2013, Proceedings. p. 43-58 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 7953 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    6 Scopus citations
  • Predictive PAC learning and process decompositions

    Shalizi, C. R. & Kontorovich, A., 1 Jan 2013, Advances in Neural Information Processing Systems. Vol. 26.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    13 Scopus citations
  • 2012

    On the learnability of shuffle ideals

    Angluin, D., Aspnes, J. & Kontorovich, A., 30 Oct 2012, Algorithmic Learning Theory - 23rd International Conference, ALT 2012, Proceedings. p. 111-123 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 7568 LNAI).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    3 Scopus citations
  • String reconciliation with unknown edit distance

    Kontorovich, A. & Trachtenberg, A., 22 Oct 2012, 2012 IEEE International Symposium on Information Theory Proceedings, ISIT 2012. p. 2751-2755 5 p. 6284024

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    3 Scopus citations
  • 2011

    Metric anomaly detection via asymmetric risk minimization

    Kontorovich, A., Hendler, D. & Menahem, E., 5 Oct 2011, Similarity-Based Pattern Recognition - First International Workshop, SIMBAD 2011, Proceedings. p. 17-30 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 7005 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    6 Scopus citations
  • 2010

    Efficient Classification for Metric Data

    Gottlieb, L. A., Kontorovich, A. & Krauthgamer, R., 2010, COLT 2010 - The 23rd Conference on Learning Theory. Kalai, A. & Mohri, M. (eds.). Omnipress, p. 433-440 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    19 Scopus citations
  • Lower bounds on learning random structures with statistical queries

    Angluin, D., Eisenstat, D., Kontorovich, L. & Reyzin, L., 19 Nov 2010, Algorithmic Learning Theory - 21st International Conference, ALT 2010, Proceedings. p. 194-208 15 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 6331 LNAI).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    3 Scopus citations
  • 2007

    Learning languages with rational kernels

    Cortes, C., Kontorovich, L. & Mohri, M., 1 Jan 2007, Learning Theory - 20th Annual Conference on Learning Theory, COLT 2007, Proceedings. Springer Verlag, p. 349-364 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 4539 LNAI).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    9 Scopus citations
  • 2006

    Learning linearly separable languages

    Kontorovich, L., Cortes, C. & Mohri, M., 1 Jan 2006, Algorithmic Learning Theory - 17th International Conference, ALT 2006, Proceedings. Springer Verlag, p. 288-303 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 4264 LNAI).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    6 Scopus citations