| Comparing recommender systems using synthetic data M Slokom Proceedings of the 12th ACM Conference on Recommender Systems, 548-552, 2018 | 23 | 2018 |
| Towards user-oriented privacy for recommender system data: A personalization-based approach to gender obfuscation for user profiles M Slokom, A Hanjalic, M Larson Information Processing & Management 58 (6), 102722, 2021 | 22 | 2021 |
| Simurec: Workshop on synthetic data and simulation methods for recommender systems research MD Ekstrand, A Chaney, P Castells, R Burke, D Rohde, M Slokom Proceedings of the 15th ACM Conference on Recommender Systems, 803-805, 2021 | 19 | 2021 |
| A new social recommender system based on link prediction across heterogeneous networks M Slokom, R Ayachi Intelligent Decision Technologies 2017: Proceedings of the 9th KES …, 2018 | 7 | 2018 |
| Partially synthetic data for recommender systems: Prediction performance and preference hiding M Slokom, M Larson, A Hanjalic arXiv preprint arXiv:2008.03797, 2020 | 6 | 2020 |
| BlurM (or) e: revisiting gender obfuscation in the user-item matrix C Strucks, M Slokom, M Larson 2019 Workshop on Recommendation in Multi-Stakeholder Environments, RMSE 2019 …, 2019 | 6 | 2019 |
| Data Masking for Recommender Systems: Prediction Performance and Rating Hiding M Slokom, M Larson, A Hanjalic ACM RecSys 2019 Late-breaking Results, (CEUR-WS.org) 2431, 2019 | 5 | 2019 |
| When machine learning models leak: an exploration of synthetic training data M Slokom, PP de Wolf, M Larson International Conference on Privacy in Statistical Databases, 283-296, 2022 | 3 | 2022 |
| Doing data right: How lessons learned working with conventional data should inform the future of synthetic data for recommender systems M Slokom, M Larson arXiv preprint arXiv:2110.03275, 2021 | 3 | 2021 |
| A hybrid user and item based collaborative filtering approach by possibilistic similarity fusion M Slokom, R Ayachi Advances in Combining Intelligent Methods: Postproceedings of the 5th …, 2016 | 3 | 2016 |
| Towards a new possibilistic collaborative filtering approach M Slokom, R Ayachi 2015 Second International Conference on Computer Science, Computer …, 2015 | 2 | 2015 |
| Gender in gender out: A closer look at user attributes in context-aware recommendation M Slokom, Ö Özgöbek, M Larson arXiv preprint arXiv:2207.14218, 2022 | 1 | 2022 |
| Machine Learning Meets Data Modification: The Potential of Pre-processing for Privacy Enchancement G Garofalo, M Slokom, D Preuveneers, W Joosen, M Larson Security and Artificial Intelligence: A Crossdisciplinary Approach, 130-155, 2022 | 1 | 2022 |
| Up close, but not too personal: Hypotargeting for recommender systems M Larson, M Slokom 1st Workshop on the Impact of Recommender Systems, ImpactRS 2019, 1-2, 2019 | 1 | 2019 |
| Check for Exploring Privacy-Preserving Techniques on Synthetic Data as a Defense Against Model Inversion Attacks Manel Slokom1, 2, 3 (), Peter-Paul de Wolf³, and Martha Larson¹ M Slokom, PP de Wolf Information Security: 26th International Conference, ISC 2023, Groningen …, 2023 | | 2023 |
| Exploring Privacy-Preserving Techniques on Synthetic Data as a Defense Against Model Inversion Attacks M Slokom, PP de Wolf, M Larson International Conference on Information Security, 3-23, 2023 | | 2023 |
| COmputer-Assisted output CHecking with Human-in-the-loop M Slokom, J Vankan, PP de Wolf, M Larson UNECE Expert meeting on Statistical Disclosure Control, 2023 | | 2023 |
| Minimizing Mindless Mentions: Recommendation with Minimal Necessary User Reviews D Stax, M Slokom, M Larson arXiv preprint arXiv:2208.03242, 2022 | | 2022 |
| Privacy and Audiovisual Content: Protecting Users as Big Multimedia Data Grows Bigger M Larson, J Choi, M Slokom, Z Erkin, G Friedland, AP de Vries Big Data Analytics for Large-Scale Multimedia Search, 183, 2019 | | 2019 |
Martha LarsonRadboud UniversityVerified email at ru.nl
