IBM Federated Learning: An Enterprise Framework White Paper v0.1 H Ludwig, N Baracaldo, G Thomas, Y Zhou, A Anwar, S Rajamoni, Y Ong, ... arXiv preprint arXiv:2007.10987, 2020 | 137 | 2020 |
The class imbalance problem FM Megahed, YJ Chen, A Megahed, Y Ong, N Altman, M Krzywinski Nature Methods, 3, 2021 | 63 | 2021 |
Context-aware data loss prevention for cloud storage services YJ Ong, M Qiao, R Routray, R Raphael 2017 IEEE 10th International Conference on Cloud Computing (CLOUD), 399-406, 2017 | 26 | 2017 |
Adaptive Histogram-Based Gradient Boosted Trees for Federated Learning YJ Ong, Y Zhou, N Baracaldo, H Ludwig arXiv preprint arXiv:2012.06670, 2020 | 21 | 2020 |
Temporal tensor transformation network for multivariate time series prediction YJ Ong, M Qiao, D Jadav 2020 IEEE International Conference on Big Data (Big Data), 1594-1603, 2020 | 10 | 2020 |
Context aware sensitive information detection M Qiao, YJ Ong, R Routray, RC Raphael US Patent 10,984,316, 2021 | 9 | 2021 |
Ibm federated learning: An enterprise framework white paper v0. 1. arXiv 2020 H Ludwig, N Baracaldo, G Thomas, Y Zhou, A Anwar, S Rajamoni, Y Ong, ... arXiv preprint arXiv:2007.10987, 0 | 7 | |
Tree-based models for federated learning systems YJ Ong, N Baracaldo, Y Zhou Federated Learning: A Comprehensive Overview of Methods and Applications, 27-52, 2022 | 5 | 2022 |
Ibm federated learning: An enterprise framework white paper v0. 1. arXiv H Ludwig, N Baracaldo, G Thomas, Y Zhou, A Anwar, S Rajamoni, Y Ong, ... arXiv preprint arXiv:2007.10987, 2020 | 5 | 2020 |
Performing multivariate time series prediction with three-dimensional transformations M Qiao, YJ Ong, D Jadav US Patent 11,768,912, 2023 | 4 | 2023 |
Federated learning technique for applied machine learning YJ Ong, Y Zhou, NB Angel US Patent App. 17/023,195, 2022 | 4 | 2022 |
Federated xgboost on sample-wise non-iid data K Jones, YJ Ong, Y Zhou, N Baracaldo arXiv preprint arXiv:2209.01340, 2022 | 3 | 2022 |
SimPO: Simultaneous Prediction and Optimization B Zhang, YJ Ong, T Nakamura arXiv preprint arXiv:2204.00062, 3, 2022 | 3 | 2022 |
Predicting Loss Risks for B2B Tendering Processes E Zahid, YJ Ong, A Megahed, T Nakamura arXiv preprint arixv:2109.06815, 2021 | 3 | 2021 |
Towards a New Science of Disinformation CS Pinhanez, GH Flores, MA Vasconcelos, M Qiao, N Linck, R de Paula, ... arXiv preprint arXiv:2204.01489, 2022 | 2 | 2022 |
Mitigating adversarial attacks for simultaneous prediction and optimization of models YJ Ong, NB Angel, A Megahed, E Chuba, Y Zhou US Patent App. 17/358,804, 2022 | 1 | 2022 |
Presenting thought-provoking questions and answers in response to misinformation N Linck, M Qiao, YJ Ong, MA Vasconcelos, CS Pinhanez, RA De Paula US Patent App. 17/184,668, 2022 | 1 | 2022 |
Predicting multivariate time series with systematic and random missing values M Qiao, YJ Ong, P Sen, B Reinwald US Patent App. 17/130,871, 2022 | 1 | 2022 |
Personalized federated learning of gradient boosted trees YJ Ong, Y Zhou, P Ram, T Salonidis, NB Angel US Patent App. 18/175,006, 2024 | | 2024 |
Joint prediction and improvement for machine learning models YJ Ong, A Megahed, MS Squillante, Y Lu, Y Liang, P Mahajan US Patent App. 17/956,065, 2024 | | 2024 |