Search results

  • 2022

    Machine Learning Meets Data Modification: The Potential of Pre-processing for Privacy Enchancement

    Garofalo, G., Slokom, M., Preuveneers, D., Joosen, W. & Larson, M., 2022, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer, p. 130-155 26 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13049 LNCS).

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  • When Machine Learning Models Leak: An Exploration of Synthetic Training Data

    Slokom, M., de Wolf, P. P. & Larson, M., 2022, Privacy in Statistical Databases - International Conference, PSD 2022, Proceedings. Domingo-Ferrer, J. & Laurent, M. (eds.). Springer, p. 283-296 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13463 LNCS).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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  • 2021

    SimuRec: Workshop on synthetic data and simulation methods for recommender systems research

    Ekstrand, M. D., Chaney, A., Castells, P., Burke, R., Rohde, D. & Slokom, M., 2021, RecSys 2021 - 15th ACM Conference on Recommender Systems. Association for Computing Machinery (ACM), p. 803-805 3 p. (RecSys 2021 - 15th ACM Conference on Recommender Systems).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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    5 Citations (Scopus)
    89 Downloads (Pure)
  • Open Access
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    10 Citations (Scopus)
    116 Downloads (Pure)
  • 2019

    BlUrM(or)e: Revisiting gender obfuscation in the user-item matrix

    Strucks, C., Slokom, M. & Larson, M., 2019, RMSE 2019 Workshop on Recommendation in Multi-stakeholder Environments: Proceedings of the Workshop on Recommendation in Multi-stakeholder Environments co-located with the 13th ACM Conference on Recommender Systems (RecSys 2019. Burke, R., Abdollahpouri, H., Malthouse, E., Thai, KP. & Zhang, Y. (eds.). CEUR-WS, p. 1-5 5 p. (CEUR Workshop Proceedings; vol. 2440).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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    89 Downloads (Pure)
  • Data masking for recommender systems: Prediction performance and rating hiding

    Slokom, M., Larson, M. & Hanjalic, A., 2019, ACM RecSys LBR 2019 ACM RecSys 2019 Late-breaking Results: Proceedings of ACM RecSys 2019 Late-breaking Results co-located with the 13th ACM Conference on Recommender Systems (RecSys 2019). Tkalcic, M. & Pera, S. (eds.). CEUR-WS, p. 21-25 5 p. (CEUR Workshop Proceedings; vol. 2431).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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  • Up close, but not too personal: Hypotargeting for recommender systems

    Larson, M. & Slokom, M., 2019, ImpactRS 2019 Impact of Recommender Systems 2019: Proceedings of the 1st Workshop on the Impact of Recommender Systems co-located with 13th ACM Conference on Recommender Systems (ACM RecSys 2019). Shalom, O. S., Jannach, D. & Guy, I. (eds.). CEUR-WS, p. 1-2 2 p. (CEUR Workshop Proceedings; vol. 2462).

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  • 2018

    Comparing recommender systems using synthetic data

    Slokom, M., 2018, RecSys '18 : Proceedings of the 12th ACM Conference on Recommender Systems. New York, NY: Association for Computer Machinery, p. 548-552 5 p.

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

    7 Citations (Scopus)