| Bayesian model-agnostic meta-learning J Yoon, T Kim, O Dia, S Kim, Y Bengio, S Ahn Advances in neural information processing systems 31, 2018 | 503 | 2018 |
| Bayesian model-agnostic meta-learning T Kim, J Yoon, O Dia, S Kim, Y Bengio, S Ahn arXiv preprint arXiv:1806.03836, 2018 | 163 | 2018 |
| How to Exploit Hyperspherical Embeddings for Out-of-Distribution Detection? Y Ming, Y Sun, O Dia, Y Li International Conference on Learning Representations (ICLR) 2023, 2023 | 159* | 2023 |
| Adversarial examples in modern machine learning: A review RR Wiyatno, A Xu, O Dia, A De Berker arXiv preprint arXiv:1911.05268, 2019 | 141 | 2019 |
| Computing System for Inferring Demographics Using Deep Learning Computations and Social Proximity on a Social Data Network ED Kim, OA Dia, K Padmanabhan, PAL Koushik US Patent App. 15/612,221, 2017 | 35 | 2017 |
| System and method for generating adversarial examples DIA Ousmane US Patent 11,157,772, 2021 | 7 | 2021 |
| Enabling inference privacy with adaptive noise injection S Kariyappa, O Dia, MK Qureshi arXiv preprint arXiv:2104.02261, 2021 | 7 | 2021 |
| Training set cleansing of backdoor poisoning by self-supervised representation learning H Wang, S Karami, O Dia, H Ritter, E Emamjomeh-Zadeh, J Chen, ... ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 6 | 2023 |
| Prediction System for Geographical Locations of Users Based on Social and Spatial Proximity, and Related Method PAL Koushik, OA Dia, K Padmanabhan US Patent App. 15/617,390, 2017 | 6 | 2017 |
| Semantics Preserving Adversarial Learning O Amadou Dia, E Barshan, R Babanezhad arXiv, arXiv: 1903.03905, 2019 | 4* | 2019 |
| Risk aware query replacement approach for secure databases performance management OA Dia, C Farkas IEEE Transactions on Dependable and Secure Computing 12 (2), 217-229, 2014 | 4 | 2014 |
| A Practical Framework for Policy Composition and Conflict Resolution OA Dia, C Farkas International Journal of Secure Software Engineering (IJSSE) 3 (4), 1-26, 2012 | 3 | 2012 |
| Localized Uncertainty Attacks O Amadou Dia, T Karaletsos, C Hazirbas, C Canton Ferrer, ... CVPR 2021 Workshop on Adversarial Machine Learning in Computer Vision, arXiv …, 2021 | 2* | 2021 |
| Retrieving Signals with Deep Complex Extractors C Trabelsi, O Bilaniuk, O Dia, Y Zhang, M Ravanelli, J Binas, ... Advances in Neural Information Processing Systems (NeurIPS) Deep Inverse …, 2019 | 1 | 2019 |
| Business driven user role assignment: nimble adaptation of RBAC to organizational changes OA Dia, C Farkas International Journal of Information Security and Privacy (IJISP) 7 (1), 45-62, 2013 | 1 | 2013 |
| On Influence Functions, Classification Influence, Relative Influence, Memorization and Generalization M Kounavis, O Dia, I Ramazanli arXiv preprint arXiv:2305.16094, 2023 | | 2023 |
| Semantics Preserving Adversarial Examples S Kariyappa, O Dia CVPR 2021 Workshop on Adversarial Machine Learning in Computer Vision, 2021 | | 2021 |
| Complex valued gating mechanisms C Trabelsi, Y Zhang, OA Dia, CJ Pal, N Rostamzadeh US Patent App. 16/556,316, 2020 | | 2020 |
| Articles for disrupting automated visual object tracking processes A Xu, O DIA, R Wiyatno R US Patent 20220058815A1, 2020 | | 2020 |
| A Simulation-based Framework for Characterizing Predictive Distributions for Deep Learning J Ai, B Gokkaya, IK Kabul, A Flower, E Emamjomeh-Zadeh, H Li, L Chen, ... ICML 2020 Workshop on Uncertainty and Robustness in Deep Learning, 2020 | | 2020 |
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARumontreal.ca의 이메일 확인됨