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2020 – today
- 2024
[c12]Simone Ooms
, Pablo César, Abdallah El Ali, Davide Ceolin, Laura Hollink, Manel Slokom, Eric J. Pauwels, Valentin Robu, Han La Poutré:
Technological Innovation in the Media Sector: Understanding Current Practices and Unraveling Opportunities. CHI Extended Abstracts 2024: 533:1-533:7- [c11]Manel Slokom, Shruti Agrawal, Nynke C. Krol, Peter-Paul de Wolf:
Relational Or Single: A Comparative Analysis of Data Synthesis Approaches for Privacy and Utility on a Use Case from Statistical Office. PSD 2024: 403-419 - [c10]Mohamed Aghaddar, Liu Nuo Su, Manel Slokom, Lucas Barnhoorn, Peter-Paul de Wolf:
A Case Study Exploring Data Synthesis Strategies on Tabular vs. Aggregated Data Sources for Official Statistics. PSD 2024: 420-435 - [i7]Manel Slokom, Laura Hollink:
How to Diversify any Personalized Recommender? A User-centric Pre-processing approach. CoRR abs/2405.02156 (2024) - [i6]Savvina Daniil, Manel Slokom, Mirjam Cuper, Cynthia C. S. Liem, Jacco van Ossenbruggen, Laura Hollink:
On the challenges of studying bias in Recommender Systems: A UserKNN case study. CoRR abs/2409.08046 (2024) - 2023
- [c9]Manel Slokom, Peter-Paul de Wolf, Martha A. Larson:
Exploring Privacy-Preserving Techniques on Synthetic Data as a Defense Against Model Inversion Attacks. ISC 2023: 3-23 - [i5]Manel Slokom, Peter-Paul de Wolf, Martha A. Larson:
When Machine Learning Models Leak: An Exploration of Synthetic Training Data. CoRR abs/2310.08775 (2023) - 2022
- [c8]Manel Slokom, Peter-Paul de Wolf, Martha A. Larson:
When Machine Learning Models Leak: An Exploration of Synthetic Training Data. PSD 2022: 283-296 - [p1]Giuseppe Garofalo, Manel Slokom, Davy Preuveneers, Wouter Joosen, Martha A. Larson:
Machine Learning Meets Data Modification - The Potential of Pre-processing for Privacy Enchancement. Security and Artificial Intelligence 2022: 130-155 - [i4]Manel Slokom, Özlem Özgöbek, Martha A. Larson:
Gender In Gender Out: A Closer Look at User Attributes in Context-Aware Recommendation. CoRR abs/2207.14218 (2022) - [i3]Danny Stax, Manel Slokom, Martha A. Larson:
Minimizing Mindless Mentions: Recommendation with Minimal Necessary User Reviews. CoRR abs/2208.03242 (2022) - 2021
- [j1]Manel Slokom, Alan Hanjalic, Martha A. Larson:
Towards user-oriented privacy for recommender system data: A personalization-based approach to gender obfuscation for user profiles. Inf. Process. Manag. 58(6): 102722 (2021) - [c7]Michael D. Ekstrand, Allison Chaney, Pablo Castells, Robin Burke, David Rohde, Manel Slokom:
SimuRec: Workshop on Synthetic Data and Simulation Methods for Recommender Systems Research. RecSys 2021: 803-805 - [i2]Manel Slokom, Martha A. Larson:
Doing Data Right: How Lessons Learned Working with Conventional Data should Inform the Future of Synthetic Data for Recommender Systems. CoRR abs/2110.03275 (2021) - 2020
- [i1]Manel Slokom, Martha A. Larson, Alan Hanjalic:
Partially Synthetic Data for Recommender Systems: Prediction Performance and Preference Hiding. CoRR abs/2008.03797 (2020)
2010 – 2019
- 2019
- [c6]Martha A. Larson, Manel Slokom:
Up Close, but not too Personal: Hypotargeting for Recommender Systems. ImpactRS@RecSys 2019 - [c5]Manel Slokom, Martha A. Larson, Alan Hanjalic:
Data Masking for Recommender Systems: Prediction Performance and Rating Hiding. RecSys (Late-Breaking Results) 2019: 21-25 - [c4]Christopher Strucks, Manel Slokom, Martha A. Larson:
BlurM(or)e: Revisiting Gender Obfuscation in the User-Item Matrix. RMSE@RecSys 2019 - 2018
- [c3]Manel Slokom:
Comparing recommender systems using synthetic data. RecSys 2018: 548-552 - 2017
- [c2]Manel Slokom, Raouia Ayachi:
A New Social Recommender System Based on Link Prediction Across Heterogeneous Networks. KES-IDT (2) 2017: 330-340 - 2015
- [c1]Manel Slokom, Raouia Ayachi:
Towards a new possibilistic collaborative filtering approach. CSCESM 2015: 209-216
Coauthor Index
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last updated on 2024-10-16 21:23 CEST by the dblp team
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