| A new and fast implementation for null space based linear discriminant analysis D Chu, GS Thye Pattern Recognition 43 (4), 1373-1379, 2010 | 73 | 2010 |
| Box drawings for learning with imbalanced data ST Goh, C Rudin Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 45 | 2014 |
| Characterization of all solutions for undersampled uncorrelated linear discriminant analysis problems D Chu, ST Goh, YS Hung SIAM Journal on Matrix Analysis and Applications 32 (3), 820-844, 2011 | 31 | 2011 |
| A new and fast orthogonal linear discriminant analysis on undersampled problems D Chu, ST Goh SIAM Journal on Scientific Computing 32 (4), 2274-2297, 2010 | 24 | 2010 |
| Variational quantum-based simulation of waveguide modes WB Ewe, DE Koh, ST Goh, HS Chu, CE Png IEEE Transactions on Microwave Theory and Techniques 70 (5), 2517-2525, 2022 | 13 | 2022 |
| Several classes of even-variable balanced Boolean functions with optimal algebraic immunity CH Tan, ST Goh IEICE transactions on fundamentals of electronics, communications and …, 2011 | 12 | 2011 |
| Learning Multi-Objective Rewards and User Utility Function in Contextual Bandits for Personalized Ranking. N Wanigasekara, Y Liang, ST Goh, Y Liu, JJ Williams, DS Rosenblum IJCAI 19, 3835-3841, 2019 | 11 | 2019 |
| A hybrid framework using a qubo solver for permutation-based combinatorial optimization ST Goh, S Gopalakrishnan, J Bo, HC Lau arXiv preprint arXiv:2009.12767, 2020 | 9 | 2020 |
| Gas turbine failure prediction utilizing supervised learning methodologies X Cai, A Chakraborty, M Evans, ST Goh, C Yuan US Patent App. 15/510,320, 2017 | 9 | 2017 |
| Techniques to enhance a QUBO solver for permutation-based combinatorial optimization ST Goh, J Bo, S Gopalakrishnan, HC Lau Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2022 | 8 | 2022 |
| Gas turbine sensor failure detection utilizing a sparse coding methodology ST Goh, C Yuan, A Chakraborty, M Evans US Patent 10,557,719, 2020 | 7 | 2020 |
| A minimax surrogate loss approach to conditional difference estimation ST Goh, C Rudin arXiv preprint arXiv:1803.03769, 2018 | 7 | 2018 |
| Qross: Qubo relaxation parameter optimisation via learning solver surrogates T Huang, ST Goh, S Gopalakrishnan, T Luo, Q Li, HC Lau 2021 IEEE 41st International Conference on Distributed Computing Systems …, 2021 | 6 | 2021 |
| Proceedings of the Genetic and Evolutionary Computation Conference Companion ST Goh, J Bo, S Gopalakrishnan, HC Lau Association for Computing Machinery, 2022 | 5 | 2022 |
| Machine learning approaches to challenging problems: interpretable imbalanced classification, interpretable density estimation, and causal inference ST Goh Massachusetts Institute of Technology, 2018 | 5 | 2018 |
| Cascaded high dimensional histograms: A generative approach to density estimation ST Goh, C Rudin arXiv preprint arXiv:1510.06779, 2015 | 2 | 2015 |
| A new and fast implementation for null space based linear discriminant analysisFJ C De-tin, TG Siong Pattern Recognition 43 (4), l1, 2010 | 2 | 2010 |
| Sparse Density Trees and Lists: An Interpretable Alternative to High-Dimensional Histograms ST Goh, L Semenova, C Rudin INFORMS Journal on Data Science, 2024 | | 2024 |
| Association Rules in QUBO Samples and Where to Find Them T Huang, ST Goh, RSM Goh, T Luo | | 2022 |
| OFFICERS: Operational Framework for Intelligent Crime-and-Emergency Response Scheduling J Chase, ST Goh, P Tran, HC Lau Proceedings of the International Conference on Automated Planning and …, 2022 | | 2022 |
