  | Wang, J. (2018). Privacy-preserving Recommender Systems Facilitated By The Machine Learning Approach [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/37026 |
Wang, J., Delerue Arriaga, A., Tang, Q., & Ryan, P. (October 2018). Facilitating Privacy-preserving Recommendation-as-a-Service with Machine Learning [Poster presentation]. the 2018 ACM SIGSAC Conference. doi:10.1145/3243734.3278504 |
 | Wang, J., & Tang, Q. (2017). Differentially Private Neighborhood-based Recommender Systems. In IFIP Information Security & Privacy Conference (pp. 14). Springer.  Peer reviewed |
 | Wang, J., & Tang, Q. (2016). A Probabilistic View of Neighborhood-based Recommendation Methods. In ICDM 2016 - IEEE International Conference on Data Mining series (ICDM) workshop CLOUDMINE. Peer reviewed |
 | Tang, Q., & Wang, J. (2016). Privacy-preserving Friendship-based Recommender Systems. IEEE Transactions on Dependable and Secure Computing. doi:10.1109/TDSC.2016.2631533 Peer reviewed |
 | Wang, J., & Tang, Q. (October 2015). Recommender Systems and their Security Concerns [Paper presentation]. iacr. |
  | Tang, Q., & Wang, J. (2015). Privacy-Preserving Context-Aware Recommender Systems: Analysis and New Solutions. In Computer Security - ESORICS 2015 - 20th European Symposium on Research in Computer Security. Peer reviewed |
 | Orlando, L.* , Ginolhac, A.* , Zhang, G., Froese, D., Albrechtsen, A., Stiller, M., Schubert, M., Cappellini, E., Petersen, B., Moltke, I., Johnson, P. L. F., Fumagalli, M., Vilstrup, J. T., Raghavan, M., Korneliussen, T., Malaspinas, A.-S., Vogt, J., Szklarczyk, D., Kelstrup, C. D., ... Willerslev, E. (2013). Recalibrating Equus evolution using the genome sequence of an early Middle Pleistocene horse. Nature, 499 (7456), 74-8. doi:10.1038/nature12323 Peer Reviewed verified by ORBi* These authors have contributed equally to this work. |