• Bingshui Da, ingshui Da, Abhishek Gupta, Yew-Soon Ong, Liang Feng, Puay-Siew Tan.
The Boom of Gene-Culture Interaction for Effective Evolutionary Multitasking. Australasian Conference on Artificial Life and Computational Intelligence (ACALCI), 2-5 February 2016, Canberra, Australia
• Wan-Yu Deng, Yew-Soon Ong, Qing-Hua Zheng.
A Fast Reduced Kernel Extreme Learning Machine. Neural Networks. 201
• A.T.W. Min, R. Sagarna, A. Gupta, O.Y. Soon and C.K. Goh,
Knowledge Transfer through Machine Learning in Aircraft Design", Computational Intelligence Magazine
• A. Gupta, J. Mandziuk, Y-S Ong,
"Evolutionary Multitasking in Bi-Level Optimization", Complex & Intelligent Systems, Vol. 1, pp. 83-95, Feb 2016.
• Y.ZHAI, Y-S Ong, and I. W. Tsang,
"Making Trillion Correlations Feasible in Feature Grouping and Selection", IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 23 Feb 2016.
• A. Gupta, Y-S Ong, L. Feng, K. C. Tan,
"Multi-Objective Multifactorial Optimization in evolutionary Multitasking", IEEE Transactions on Cybernetics, May 2016.
• A. Gupta, Y-S Ong, P. A. Kelly, C. K. Goh,
"Pareto Rank Learning for Multi-Objective Bi-Level Optimization: A Study in Composites Manufacturing", 2016 IEEE World Congress on Computational Intelligence, Vancouver, Canada, July 2016.
• A. Gupta, Y-S Ong, B. Da, L. Feng, D. Handoko,
"Measuring Complementarity between Function Landscapes in Evolutionary Multitasking", 2016 IEEE World Congress on Computational Intelligence, Vancouver, Canada, July 2016.
• P. Wei, Y. Ke, C-K Goh,
"Deep Nonlinear Feature Coding for Unsupervised Domain Adaptation", 2016 International Joint Conference on Artificial Intelligence, New Work, USA, July 2016.
• R. Chandra, A. Gupta, Y-S Ong and C-K. Goh,
“Evolutionary multi-task learning for modular training of feedforward neural networks”, 23rd International Conference on Neural Information Processing, Kyoto, Japan, October 16-21, 2016.
• R. Sagarna, Y-S Ong,
“Concurrently Searching Branches in Software Tests Generation through Multitask Evolution”, 2016 IEEE Symposium Series on Computational Intelligence, Athens, Greece, December 6-9, 2016.
• Y. Liu, X. Li, A. W-K Kong, C-K Goh,
"Learning from small data: a pairwise approach for ordinal regression", 2016 IEEE Symposium Series on Computational Intelligence, Athens, Greece, December 6-9, 2016.
• D. Lim, Y-S Ong, A. Gupta, C.K. Goh, P. Dutta,
"Towards A New Praxis in Optinformatics for Evolutionary Computation: Simultaneous Problem Learning and Optimization", Evolutionary Intelligence, Sep 2016.
• A.T.W. Min, R. Sagarna, A. Gupta, R. Chandra, and Y-S Ong,
"Coping with Data Scarcity in Aircraft Engine Design", AIAA AVIATION 2017, Denver, Colorado, USA, 5–9 June 2017
• Y. Liu, A. W-K Kong and C-K Goh,
"Deep Ordinal Regression based on Data Relationship for Small Datasets", Twenty-sixth International Joint Conference on Artificial Intelligence (IJCAI-17), Melbourne, Australia, 19-25 August 2017
• P. Wei, R. Sagarna, Y. Ke, Y-S Ong and C-K Goh,
"Source-Target Similarity Modelings for Multi-Source Transfer Gaussian Process Regression", 34th International Conference on Machine Learning (ICML 2017), Sydney, Australia, 6 - 11 August, 2017
• P.Wei, Y. Ke, and C-K Goh,
"Domain Specific Feature Transfer for Hybrid Domain Adaptation", IEEE International Conference on Data Mining (ICDM) 2017, New Orleans, USA, 18-21 November, 2017.
• Yanzhu Liu, Adams Kong and Chi Keong Goh,
"A Constrainted Deep Neral Network for Ordinal Regression" Computer Vision and Pattern Recognition 2018 (CVPR) Jun 19, 2018 - Jun 21, Salt Lake City, USA
• A.T.W. Min, Y-S Ong, A Gupta and C-K Goh,
"Transfer Evolutionary Multiobjective Optimization for Computationally Expensive Problems using Multi-Problem Surrogates", IEEE Transactions on Evolutionary Computation