| When Gaussian process meets big data: A review of scalable GPs H Liu, YS Ong, X Shen, J Cai IEEE transactions on neural networks and learning systems 31 (11), 4405-4423, 2020 | 1179 | 2020 |
| Multifactorial evolution: Toward evolutionary multitasking A Gupta, YS Ong, L Feng IEEE Transactions on Evolutionary Computation 20 (3), 343-357, 2015 | 1025 | 2015 |
| Meta-Lamarckian learning in memetic algorithms YS Ong, AJ Keane IEEE transactions on evolutionary computation 8 (2), 99-110, 2004 | 808 | 2004 |
| Evolutionary optimization of computationally expensive problems via surrogate modeling YS Ong, PB Nair, AJ Keane AIAA journal 41 (4), 687-696, 2003 | 714 | 2003 |
| Classification of adaptive memetic algorithms: a comparative study YS Ong, MH Lim, N Zhu, KW Wong IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 36 …, 2006 | 677 | 2006 |
| A multi-facet survey on memetic computation X Chen, YS Ong, MH Lim, KC Tan IEEE Transactions on evolutionary computation 15 (5), 591-607, 2011 | 600 | 2011 |
| Wrapper–filter feature selection algorithm using a memetic framework Z Zhu, YS Ong, M Dash IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 37 …, 2007 | 589 | 2007 |
| Markov blanket-embedded genetic algorithm for gene selection Z Zhu, YS Ong, M Dash Pattern Recognition 40 (11), 3236-3248, 2007 | 564 | 2007 |
| Generalizing surrogate-assisted evolutionary computation D Lim, Y Jin, YS Ong, B Sendhoff IEEE Transactions on Evolutionary Computation 14 (3), 329-355, 2009 | 553 | 2009 |
| A survey of adaptive sampling for global metamodeling in support of simulation-based complex engineering design H Liu, YS Ong, J Cai Structural and Multidisciplinary Optimization 57 (1), 393-416, 2018 | 540 | 2018 |
| Combining global and local surrogate models to accelerate evolutionary optimization Z Zhou, YS Ong, PB Nair, AJ Keane, KY Lum IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and …, 2006 | 520 | 2006 |
| Multifactorial evolutionary algorithm with online transfer parameter estimation: MFEA-II KK Bali, YS Ong, A Gupta, PS Tan IEEE Transactions on Evolutionary Computation 24 (1), 69-83, 2019 | 469 | 2019 |
| Extreme learning machines [trends & controversies] E Cambria, GB Huang, LLC Kasun, H Zhou, CM Vong, J Lin, J Yin, Z Cai, ... IEEE intelligent systems 28 (6), 30-59, 2013 | 468 | 2013 |
| Multiobjective multifactorial optimization in evolutionary multitasking A Gupta, YS Ong, L Feng, KC Tan IEEE transactions on cybernetics 47 (7), 1652-1665, 2016 | 464 | 2016 |
| Evolutionary multitasking via explicit autoencoding L Feng, L Zhou, J Zhong, A Gupta, YS Ong, KC Tan, AK Qin IEEE transactions on cybernetics 49 (9), 3457-3470, 2018 | 451 | 2018 |
| A fast pruned-extreme learning machine for classification problem HJ Rong, YS Ong, AH Tan, Z Zhu Neurocomputing 72 (1-3), 359-366, 2008 | 444 | 2008 |
| Consistencies and contradictions of performance metrics in multiobjective optimization S Jiang, YS Ong, J Zhang, L Feng IEEE transactions on cybernetics 44 (12), 2391-2404, 2014 | 412 | 2014 |
| Insights on transfer optimization: Because experience is the best teacher A Gupta, YS Ong, L Feng IEEE Transactions on Emerging Topics in Computational Intelligence 2 (1), 51-64, 2017 | 407 | 2017 |
| CAN-PINN: A fast physics-informed neural network based on coupled-automatic–numerical differentiation method PH Chiu, JC Wong, C Ooi, MH Dao, YS Ong Computer Methods in Applied Mechanics and Engineering 395, 114909, 2022 | 375 | 2022 |
| Remarks on multi-output Gaussian process regression H Liu, J Cai, YS Ong Knowledge-Based Systems 144, 102-121, 2018 | 371 | 2018 |
