Conference Papers

 
  1. J. Dong, P. Koniusz, J. Chen, J. Wang, and Y. S. Ong, 'Robust Distillation via Untargeted and Targeted Intermediate Adversarial Samples', IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR-2024), June 17-21, 2024, Seattle, USA.
  2. J. Dong, P. Koniusz, J. Chen, X. Xie, and Y. S. Ong, 'Adversarially Robust Few-shot Learning via Parameter Co-distillation of Similarity and Class Concept Learners',, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR-2024), June 17-21, 2024, Seattle, USA.
  3. W. Liu, C. Chen, X. Liao, M. Hu, Y. Tan, F. Wang, X. Zheng, and Y. S. Ong, 'Learning Accurate and Bidirectional Transformation via Dynamic Embedding Transportation for Cross-Domain Recommendation', The 38th Annual AAAI Conference on Artificial Intelligence. February 20-27, 2024, Vancouver, Canada Vancouver Convention Centre, West Building.
  4. S. Tan, H. Cheng, X. Wu, H. Yu, T. He, Y. S. Ong, C. Wang and X. Tao, 'FedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants', The 38th Annual AAAI Conference on Artificial Intelligence. February 20-27, 2024, Vancouver, Canada Vancouver Convention Centre, West Building.
  5. X. Qu, H. Liu, Z. Sun, X. Yin, Y. S. Ong, L. Lu and Z. Ma, 'Towards Building Voice-based Conversational Recommender Systems: Datasets, Potential Solutions, and Prospects', The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 23-27 July 2023, Taipei.
  6. L. Cao, H. Chen, X. Fan, J. Gama, Y. S. Ong and V. Kumar, 'Bayesian Federated Learning: A Survey', The 32nd International Joint Conference on Artificial Intelligence, 19th-25th August 2023, Macao. Available here as PDF file.
  7. J. Xie, W. Li, X. Zhan, Z. Liu, Y. S. Ong and C. C. Loy, 'Masked Frequency Modeling for Self-Supervised Visual Pre-Training', The International Conference on Learning Representations (ICLR-2023). Available here as PDF file.
  8. Q. Fu, Q. Xu, Y. S. Ong and W. Tao, 'Geo-Neus: Geometry-Consistent Neural Implicit Surfaces Learning for Multi-view Reconstruction', Thirty-Sixth Conference on Neural Information Processing Systems (NeurIPS 2022), Nov 28 - Dec 09, 2022.
  9. X. Qu, Y. S. Ong, A. Gupta, P. Wei, Z. Sun and Z. Ma, 'Importance Prioritized Policy Distillation', The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022), August 14-18, 2022 - Washington D.C.
  10. X. Qu, M. Gao, Z. Sun, Y. S. Ong and Z. Ma, 'Synthesising Audio Adversarial Examples for Automatic Speech Recognition', The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022), August 14-18, 2022 - Washington D.C.
  11. A. Chan and Y. S. Ong, 'How Does Frequency Bias Affect the Robustness of Neural Image Classifiers against Common Corruption and Adversarial Perturbations?', 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI-ECAI 2022), July 23-29, 2022, Messe Wien, Vienna, Austria.
  12. A. Gupta, R. Lim, C. C. Ooi and Y. S. Ong, 'Tightening Regret Bounds for Scalable Transfer Optimization with Gaussian Process Surrogates', IEEE Symposium Series on Computational Intelligence (SSCI), December 4-7, 2022, Singapore.
  13. Z. Sun, J. Yang, H. Fang, X. Qu and Y. S. Ong, 'Revisiting Bundle Recommendation: Datasets, Tasks, Challenges and Opportunities for Intent-aware Product Bundling', 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, July 11-15, 2022, Madrid.
  14. J. Xie, X. Zhan, Z. Liu, Y. S. Ong, 'Unsupervised Object-Level Representation Learning from Scene Images', Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021), Dec 06-14, 2021.Available here as PDF file.
  15. T. T. He, Y. S. Ong and L. Bai, 'Learning Conjoint Attentions for Graph Neural Nets', Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021), Dec 06-14, 2021. Available here as PDF file.

  16. A. Chan and Y. S. Ong, 'A Self-Supervised Approach for Controlled Text Generation', The International Conference on Learning Representations (ICLR-2021), 4-8 May, 2021. The International Conference on Learning Representations (ICLR-2021), 4-8 May, 2021.
  17. A. Chan, Y. Tay and Y. S. Ong, and A. Zhang, 'Poison Attacks against Text Datasets with Conditional Adversarially Regularized Autoencoder', The 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP-Findings 2020), 16th - 20th November 2020. Available here as PDF file
  18. A. Chan, Y. Tay and Y. S. Ong, 'What it Thinks is Important is Important: Robustness Transfers through Input Gradients', IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR-2020), 16-18 June, 2020, Seattle, Washington. Available here as PDF file
  19. X. Zhan, J. Xie, Z. Liu, Y. S. Ong, and C. C. Loy, 'Online Deep Clustering for Unsupervised Representation Learning', IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR-2020), 16-18 June, 2020, Seattle, Washington. Available here as PDF file
  20. A. Chan, Y. Tay, Y. S. Ong,, and J. Fu, 'Jacobian adversarially regularized networks for robustness', The International Conference on Learning Representations (ICLR-2020), 26-30 April, 2020, Millennium Hall, Addis Ababa Ethiopia. Available here as PDF file
  21. M. Das, M. Pratama, J. Zhang and Y. S. Ong, 'Skip-connected Evolving Recurrent Neural Network for Data Stream Classification under Label Latency Scenario', Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), February 7-12, 2020, Hilton New York Midtown, New York, New York, USA.
  22. A. Gupta, Y. S. Ong, M. Shakeri, X. Chi and A. Zhang, 'Blessing of Dimensionality: How Many-Objective Search Supports Inverse Modeling', 2019 IEEE International Conference on Big Data (IEEE BigData 2019), Los Angeles, CA, USA. Available here as PDF file.
  23. M. Shakeri, A. Gupta, Y. S. Ong, X. Chi and A. Zhang, 'Coping with Big Data in Transfer Optimization', 2019 IEEE International Conference on Big Data (IEEE BigData 2019), Los Angeles, CA, USA.
  24. T. T. He, L. Bai and Y. S. Ong, 'Manifold Regularized Stochastic Block Model', 31st IEEE International Conference on Tools with Artificial Intelligence (ICTAI-19), November 4-6, 2019, Portland, Oregon, US. - *Nikolaos Bourbakis - CV Ramamoorthy ICTAI-2019 Best Paper Recognition Award*.
  25. P. Wei, R. Sagarna, Y. Ke and Y. S. Ong, 'Unclutterd Domain Sub-similarity for Transfer Regression', International Conference on Data Mining (ICDM-18), November 17-20, 2018, Singapore.
  26. H. Liu, J. F. Cai, Y. Wang and Y. S. Ong, 'Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression', 35th International Conference on Machine Learning (ICML 2018), July 10-15, 2018, Stockholm, Sweden.
  27. X. Shen, S. Pan, W. Liu, Y. S. Ong, and Q. S. Sun, 'Discrete Network Embedding', 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI 2018), July 13-19, 2018, Stockholm, Sweden.
  28. X. Shen, W. Liu, Y. Luo, Y. S. Ong, and I. W. Tsang, 'Deep Binary Prototype Multi-label Learning', 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI 2018), July 13-19, 2018, Stockholm, Sweden.
  29. Z. Zeng, X. Fan, C. Y. Miao, C. Leung, J. J. Chin, and Y. S. Ong, 'Context-based and Explainable Decision Making with Argumentation', International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2018), July 10-15, 2018, Stockholm, Sweden.
  30. X. Shen, W. Liu, I. Tsang, Q.S. Sun and Y. S. Ong, 'Compact Multi-label Learning', Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018), Feb 2-7, 2018, New Orleans, Lousiana, USA.
  31. P. Wei, R. Sagarna, Y. Ke, Y. S. Ong, and C. K. Goh, 'Source-Target Similarity Modelings for Multi-Source Transfer Gaussian Process Regression', International Conference on Machine Learning (ICML 2017), August 6-11, 2017.
  32. H. Yang, J. T. Zhou, J. Cai and Y. S. Ong, 'MIML-FCN+: multi-instance multi-label learning via fully convolutional networks with privileged information', IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
  33. K. Bali, A. Gupta, L. Feng, Y. S. Ong, and P. S. Tan, 'Linearized Domain Adaptation in Evolutionary Multitasking', IEEE Congress on Evolutionary Computation, Spain, June 5-8, 2017, Available here to download the paper.
  34. L. Zhou, L. Feng, A. Gupta, Y. S. Ong, K. Liu, C. Chen, E. Sha, B. Yang and B. W. Yan, 'Solving Dynamic Vehicle Routing Problem via Evolutionary Search with Learning Capability', IEEE Congress on Evolutionary Computation, Spain, June 5-8, 2017.
  35. A. Tan, R. Sagarna, A. Gupta, R. Chandra and Y. S. Ong, ' Coping with Data Scarcity in Aircraft Engine Design', 18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, 2017 AIAA Aviation and Aeronautics Forum and Exposition, Denver, Colorado, 5-9 June 2017.
  36. A. Gupta and Y. S. Ong, 'Genetic Transfer or Population Diversification? Deciphering the Secret Ingredients of Evolutionary Multitask Optimization', SSCI 2016.
  37. R. Sagarna and Y. S. Ong, 'Concurrently Searching Branches in Software Tests Generation through Multitask Evolution', SSCI 2016.
  38. L. Zhou, L. Feng, J. Zhong, Y. S. Ong, Z. Zhu and E. Sha, 'Evolutionary Multitasking in Combinatorial Search Spaces: A Case Study in Capacitated Vehicle Routing Problem', SSCI 2016.
  39. Y. Yuan, Y. S. Ong, A. Gupta, P. S. Tan and H. Xu, 'Evolutionary Multitasking in Permutation-Based Combinatorial Optimization Problems: Realization with TSP, QAP, LOP, and JSP', IEEE TENCON 2016.
  40. Y. Hou, Y. Zeng and Y. S. Ong,'A Memetic Multi-Agent Demonstration Learning Approach with Behavior Prediction', International conference on autonomous agents and multiagent systems, Singapore, May 9-13, 2016.
  41. S. Badsha, A. K. Qin, Y. Ren, J. Chan and Y. S. Ong, 'Data Mining Assisted Performance Comparison and Visualization for Evolutionary Algorithms', IEEE WCCI-CEC 2016, Vancouver, Canada.
  42. Z. Ye, L. Feng, Y. S. Ong, K. Liu, C. Chen and E. Sha, 'A Preliminary Study on Distance Selection in Probabilistic Memetic Framework for Capacitated Arc Routing Problem', IEEE WCCI-CEC 2016, Vancouver, Canada.
  43. S. Jiang, L. Feng, D. Yang, Y. S. Ong, A. N. Zhang, P. S. Tan, Z. Cai and C. K. Heng, 'Towards Adaptive Weight Vectors for Multiobjective Evolutionary Algorithm by Decomposition', IEEE WCCI-CEC 2016, Vancouver, Canada.
  44. S. Jiang, L. Feng, K. H., Q. C. Nguyen, Y. S. Ong, A. N. Zhang and P. S. Tan, 'Adaptive Indicator-based Evolutionary Algorithm for Multiobjective Optimization Problems', IEEE WCCI-CEC 2016, Vancouver, Canada.
  45. A. Gupta,, Y. S. Ong, B. Da, L. Feng and D. Handoko, 'Landscape Synergy in Evolutionary Multitasking', IEEE WCCI-CEC 2016, Vancouver, Canada.
  46. H. C. Kim, A. Gupta, B. Da, Y. S. Ong, Q. C. Nguyen, S. Jiang and P. S. Tan, 'Application of Route Flexibility in Data-Starved Vehicle Routing Problem with Time Windows', IEEE WCCI-CEC 2016, Vancouver, Canada.
  47. B. Da, A. Gupta Y. S. Ong, and L. Feng, 'Evolutionary Multitasking across Single and Multi-Objective Formulations for Improved Problem Solving', IEEE WCCI-CEC 2016, Vancouver, Canada.
  48. Y. Hou, L. Feng and Y. S. Ong, 'Creating Human-Like Non-Player Game Characters using A Memetic Multi-Agent System', IEEE WCCI-CEC 2016, Vancouver, Canada.
  49. C. S. Chen, Y. Hou and Y. S. Ong, 'A Conceptual Modeling of Flocking-regulated Multi-agent Reinforcement Learning', IEEE WCCI-CEC 2016, Vancouver, Canada.
  50. S. D. Handako, A Gupta, H. C. Kim, L. H. Chuin, Y. S. Ong, and P. S. Tan, 'Solving multi-vehicle profitable tour problem via knowledge adoption in evolutionary bilevel programming', IEEE CEC 2015, May 25-28, 2015, Sendai, Japan.
  51. A. Gupta and Y. S. Ong,'An Evolutionary Algorithm with Adaptive Scalarization for Multiobjective Bilevel Programs', IEEE CEC 2015, May 25-28, 2015, Sendai, Japan.
  52. Y. Ding, P. Zhao, S. C.H. Hoi and Y. S. Ong,'An Adaptive Gradient Method for Online AUC Maximization', Twenty-Ninth AAAI Conference on Artificial Intelligence 2015, January 25-29, 2015, Austin Texas, USA.
  53. W.Y. Deng and Y. S. Ong,'Online Sequential Kernel Extreme Learning Machine', The International Conference on Extreme Learning Machines (ELM2014), Marina Bay Sands, Singapore, December 8-10, 2014.
  54. W.Y. Deng, C. L. Su and Y. S. Ong,'Access Behavior Prediction in Distributed Storage System using Regularized Extreme Learning Machine', The International Conference on Extreme Learning Machines (ELM2014), Marina Bay Sands, Singapore, December 8-10, 2014.
  55. A. Gupta, Y. S. Ong, A. Zhang and P. S. Tan,'A Bi-level Evolutionary Algorithm for Multi-Objective Vehicle Routing Problems with Time Window Constraints', The 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES2014), 10-12 Nov 2014.
  56. G. Yee, Y. S. Ong, and P. S. Tan,'Emergent Effects from Simple Mechanisms in Supply Chain Models', The 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES2014), 10-12 Nov 2014.
  57. A. Kattan, M. Kampouridis Y. S. Ong, and K. Mehamdi, 'Transformation of Input Space using Statistical Moments: EA-Based Approach', IEEE Congress on Evolutionary Computation, Accepted 2014.
  58. S. W. Jiang, J. Zhang and Y. S. Ong, 'A Pheromone-based Traffic Management Model for Vehicle Re-routing and Traffic Light Control', International conference on autonomous agents and multiagent systems, 2014.
  59. X. S. Chen, Y. S. Ong, L. Feng, M. H. Lim, C. S. Chen and C S. Ho, 'Memetic Ant Colony System for Resource Gathering on Navigation Graph', The 17th Asia Pacific Symposium on Intelligent and Evolutionary Systems, 2013.
  60. X. S. Chen, Y. S. Ong, P. S. Tan, N. S. Zhang and Z. P. Li, 'Agent-Based Modeling and Simulation for Supply Chain Risk Management - A Survey of the State-of-the-Art', IEEE Systems, Man & Cybernetics Conference, 2013.
  61. Z. P. Li, P. S. Tan, N. S. Zhang, Q. M. Yee, N. Q. Chinh, Y. S. Ong, and X. S. Chen, 'A Review of Complex Systems Technologies for Supply Chain Risk Management', IEEE Systems, Man & Cybernetics Conference, 2013.
  62. N. Q. Chinh, Z. P. Li, P. S. Tan, X. S. Chen and Y. S. Ong,, 'An agent-based simulation to quantify and analyze bullwhip effects in supply chains', IEEE Systems, Man & Cybernetics Conference, 2013.
  63. X. Chen, Y. Zeng, Y. S. Ong, C. S. Ho and Y. Xiang, 'A Study on Like-attracts-Like versus Elitist Selection Criterion for Human-like Social behavior of Memetic Multiagent System', IEEE Congress on Evolutionary Computation, June 2013.
  64. A. Kattan, Y. S. Ong, and E. Galvan, 'Multi-Agent Multi-Issue Negotiations with Incomplete Information: A Genetic Algorithm Based on Discrete Surrogate Approach', IEEE Congress on Evolutionary Computation, June 2013.
  65. J. Mandziuk, Y. S. Ong, and K. Waledzik, 'Multi-Game Playing - a Challenge for Computational', IEEE Symposium Series on Computational Intelligence, April 2013.
  66. S. W. Jiang, J. Zhang and Y. S. Ong, 'An Evolutionary Model for Constructing Robust Trust Networks', The 12th International conference on autonomous agents and multiagent systems, 2013.
  67. G. Zhang, Y. Wen and Y. S. Ong, 'Near-optimal packet allocation algorithm for content uploading to media cloud via collaborative wireless network', International Conference on Computing, Networking and Communications (ICNC), pps., 762 - 767, 2013.
  68. C. W. Seah, Ivor W. Tsang, Y. S. Ong, and Q. Mao, 'Learning Target Predictive Function without Target Labels', Proceedings of the IEEE International Conference on Data Mining (ICDM), 2012. Available here as PDF file.
  69. C. S. Ho, Y. S. Ong, M. H. Lim, X. S. Chen and A. H. Tan 'FAME, Soft flock formation control for collective behavior studies and rapid games development', The Ninth International Conference on Simulated Evolution And Learning (SEAL'2012). Available here as PDF file.
  70. Y. Zhai, M. K. Tan, I. W. Tsang and Y. S. Ong, 'Discovering Support and Affiliated Features from Very High Dimensions', International Conference on Machine Learning (ICML 2012), June 2012. Available here as PDF file.
  71. F. Liang, Y. S. Ong, I. W. Tsang and A.-H. Tan, 'An Evolutionary Search Paradigm that Learns with Past Experiences', IEEE Congress on Evolutionary Computation, June 2012. *Nominated for Best Student Paper Award*.
  72. A. K. Qin, F. Raimondo, F. Forbes andY. S. Ong, 'An Improved CUDA-Based Implementation of Differential Evolution on GPU', ACM Genetic and Evolutionary Computations (GECCO 2012), July 2012. *Nominated for Best Paper Award*. PDF file.
  73. M. M. H. Ellabaan and Y. S. Ong, 'Experiences on Memetic Computation for Locating Transition States in Biochemical Applications', ACM Genetic and Evolutionary Computations (GECCO 2012), July 2012. Available here as PDF file.
  74. M. N. Le, Y. S. Ong, C. W. Seah, S. Menzel and B. Sendhoff, 'Multi Co-objective Evolutionary Optimization: Cross Surrogate Augmentation for Computationally Expensive Problems' , IEEE Congress on Evolutionary Computation, June 2012. Available here as PDF file.
  75. H. E. Huang, Y. S. Ong,and X. S. Chen, 'Autonomous Flock Brush for Non-Photorealistic Rendering', IEEE Congress on Evolutionary Computation, June 2012. *Nominated for Best Student Paper Award*. Available here as PDF file.
  76. C. W. Seah, Y. S. Ong, I. W. Tsang and S. W. Jiang, 'Rank Learning in Multi-objective Evolutionary Algorithms', IEEE Congress on Evolutionary Computation, June 2012. Available here as PDF file.
  77. S. W. Jiang, J. Zhang and Y. S. Ong, 'A Multiagent Evolutionary Framework based on Trust for Multiobjective Optimization', The 11th international conference on autonomous agents and multiagent systems, June 2012. Available here as PDF file.
  78. C.-W. Seah, I. W. Tsang and Y. S. Ong,. 'Healing Sample Selection Bias by Source Classifier Selection', IEEE International Conference on Data Mining (IEEE ICDM 2011), Vancouver, Canada, Dec 2011. [Full Paper, Acceptance rate = 13%] Available here as PDF file.
  79. S. W. Jiang, J. Zhang and Y. S. Ong, 'Asymmetric Pareto-adaptive Scheme for Multiobjective Optimization', The 24th Australasian Joint Conference on Artificial Intelligence, December 2011. Available here as PDF file.
  80. M. Dash and Y. S. Ong, 'RELIEF-C: Efficient Feature Selection for Clustering over Noisy Data', IEEE International Conference on Tools with Artificial Intelligence (ICTAI), pp. 869-872, 2011.
  81. S. W. Jiang, J. Zhang and Y. S. Ong, 'Multiobjective Optimization by Decomposition with Pareto-adaptive Weight Vectors', Seventh International Conference on Natural Computation, 2011. Available here as PDF file.
  82. L. Feng, Y. S. Ong, A.-H. Tan and X.-S. Chen, 'Towards Human-like Social Multi-agents with Memetic Automaton', IEEE Congress on Evolutionary Computation, June 5-8, 2011. Available here as PDF file.
  83. S. D. Handoko, C. K. Kwoh and Y. S. Ong,'Classification-assisted Memetic Algorithms for Equality-constrained Optimization Problems with Restricted Constraint Function Mapping', IEEE Congress on Evolutionary Computation, June 5-8, 2011. Available here as PDF file.
  84. C.S. Ho, Q.H. Nguyen, Y. S. Ong, and X. Chen, 'Autonomous multi-agents in flexible flock formation', Lecture Notes in Computer Science, 6459 LNCS, pp. 375-385, 2010. Available here as PDF file.
  85. C.-W. Seah, I. W. Tsang, Y. S. Ong, K.-K. Lee, 'Predictive Distribution Matching SVM for Multi-Domain Learning', European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2010), Barcelona, Spain, September 2010. Available here as PDF file.
  86. Chua, Z.-Y., Kang, Y., Jiang, X., Pang, K.-H., Gregory, A.C., Tan, C.-Y., Wong, W.-L., Y. S. Ong, Miao, C.-Y., 'Youth Olympic village Co-Space', 2010 Proceedings - 2010 International Conference on Cyberworlds, pp. 200-207, 2010.
  87. Pan, Z., Feng, L., Y. S. Ong, Kang, Y., Tan, A.-H., Miao, C.-Y., 'Meme selection, Variation, and Transmission in Multi-agent System', World Automation Congress, 2010.
  88. Doan, V.K., Lim, M.H., Y. S. Ong,., Jang, J.S., Vavrina, M.A., Vian, J.L. and Barhorst, J., 'Turning time estimation model for region coverage', International Conference on Computational Problem-Solving, pp. 203-208, 2010. *Best Student Paper Award*.
  89. Song, L.Q., Lim, M.H., Y. S. Ong, 'Neural meta-memes framework for combinatorial optimization', Lecture Notes in Computer Science, 6466 LNCS, pp. 198-205, 2010.
  90. L. Feng, Y. S. Ong,,, Q. H. Nguyen and A.-H. Tan, 'Towards Probabilistic Memetic Algorithm: An Initial Study on Capacitated Arc Routing Problem', IEEE World Congress on Computational Intelligence, Congress on Evolutionary Computation 2010, Barcelona, Spain, 18-23, 2010. Available here as PDF file. 
  91. D. Lim, Y. S. Ong,, R. Setiawan and M. Idris, 'Classifier-assisted Constrained Evolutionary Optimization for Automated Geometry Selection of Orthodontic Retraction Spring', IEEE World Congress on Computational Intelligence, Congress on Evolutionary Computation 2010, Barcelona, Spain, 2010. Available here as PDF file. 
  92. M. M. H. Ellabaan, Y. S. Ong,, M. H. Lim and J.-L. Kuo, 'Finding Multiple First Order Saddle Points Using a Valley Adaptive Clearing Genetic Algorithm', IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA'09), Daejeon, Korea, pps.457-462, Dec 2009. Available here as PDF file. 
  93. M. M. H. Ellabaan and Y. S. Ong, 'Valley-Adaptive Clearing Scheme for Multimodal Optimization Evolutionary Search', 9th International Conference on Intelligent Systems Design and Applications (ISDA'09), Pisa, Italy,  pps.1-6, Dec 2009. Available here as PDF file.
  94. S . Handoko, C. K. Kwoh and Y. S. Ong, 'Classification-Assisted Memetic Algorithms for Equality-Constrained Optimization Problems', AI 2009: Advances in Artificial Intelligence, Lecture Notes in Computer Science, vol. 5866, pps.391-400, 2009. Available here as PDF file.
  95. A.-D. Do, S.-Y. Cho and Y. S. Ong, 'A Multi-Objective Memetic Algorithm Based Clustering Method', International Conference on Artificial Intelligence, ICAI 2008, July, pps.881-887, 2008.
  96. M. N. Le and Y. S. Ong,, 'A Frequent Pattern Mining Algorithm for Understanding Genetic Algorithms', International Conference on Intelligent Computing (ICIC) 2008, Shanghai, China, Sept 2008. Available here as PDF file. 
  97. D. Lim, Y. S. Ong,,, Y. Jin, and B. Sendhoff, 'Evolutionary Optimization with Dynamic Fidelity Computational Model', International Conference on Intelligent Computing (ICIC) 2008, Shanghai, China, Sept 2008. Available here as PDF file.  
  98. D. Mallick, Vincent C.S. Lee and Y. S. Ong,, 'An Empirical Study of Genetic Programming Generated Trading Rules in Computerized Stock Trading Service System', Proceedings of IEEE 5th ICSSSM'08, 30 June - 2 July 2008, Melbourne. Available here as PDF file.  
  99. Q. H. Nguyen, Y. S. Ong,,and M. H.  Lim, 'Non-genetic transmission of memes by diffusion', Genetic and Evolutionary Computation Conference, Atlanta, Georgia, US, 12-16 July 2008, ACM Press. Available here as PDF file.  
  100. M. N. Le, Y. S. Ong,,and Q. H. Nguyen, 'Optinformatics for Schema Analysis of Binary Genetic Algorithms', Genetic and Evolutionary Computation Conference, Atlanta, Georgia, US, 12-16 July 2008, ACM Press. Available here as PDF file.  
  101. S . Handoko, C. K. Kwoh and Y. S. Ong,,, 'Using Classification for Constrained Memetic Algorithm: A New Paradigm', 2008, IEEE International Conference on Systems, Man, and Cybernetics 2008. Available here as PDF file.  
  102. S . Handoko, C. K. Kwoh and Y. S. Ong,,, 'A Study on Constrained MA Using GA and SQP: Analytical Vs. Finite-difference Gradients', 2008 IEEE World Congress on Computational Intelligence. Available here as PDF file.  
  103. C. K. Goh, Y. S. Ong,,and K. C. Tan, 'An Investigation on Evolutionary Gradient Search for Multi-objective Optimization', 2008 IEEE World Congress on Computational Intelligence. Available here as PDF file.  
  104. Y. Xu, M. H. Lim, Y. S. Ong,,, 'Automatic Configuration of Metaheuristic Algorithms for Complex Combinatorial Optimization Problems', 2008 IEEE World Congress on Computational Intelligence.  
  105. Z. Zhu and Y. S. Ong,,, 'Memetic Algorithms For Feature Selection On Microarray Data', Fourth International Symposium on Neural Networks, Vol. 4491/2007, pp. 1327-1335, June 3-7, 2007, Nanjing, China. Available here as PDF file.  
  106. D. Lim, Y. S. Ong,,, Y. Jin and B. Sendhoff, 'A Study on Metamodeling Techniques, Ensembles, and Multi-Surrogates in Evolutionary Computation', Genetic and Evolutionary Computation Conference. London, UK, pp. 1288 - 1295, 2007, ACM Press. Available here as PDF file or from ACM Press.  
  107. C. K. Goh, K. C. Tan, C. Y. Cheong and Y. S. Ong,, 'Noise-induced features in robust multi-objective optimization problems', 2007 IEEE Congress on Evolutionary Computation, CEC 2007, Article number 4424521, Pages 568-575.  
  108. J. Tang, L. Song, M. H. Lim and Y. S. Ong,, 'Hierarchical Model Parallel Memetic Algorithm in Heterogeneous Computing Environment', 2007 IEEE Congress on Evolutionary Computation, CEC 2007, Article number 4424820, Pages 2758-2765.  
  109. Q. H. Nguyen, Y. S. Ong,,and N. Krasnogor, 'A study on the design issues of Memetic Algorithm', 2007 IEEE Congress on Evolutionary Computation, CEC 2007, Article number 4424770, Pages 2390-2397. Available here as PDF file.  
  110. E. P. Sulaiman, Y. S. Ong,, M. Salahuddin and T. Hung, 'A Flow Model of Web Services For The Grid', GCA 2007, pp. 65-75, Singapore.  
  111. H. Soh, Y. S. Ong,,, M. Salahuddin, T. Hung and B. S. Lee, ‘Playing in the Objective Space: Coupled Approximators for Multi-Objective Optimization’, IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making, pp. 325-332, April 2007. Available here as PDF file
  112. M. Salahuddin, T. Hung, H. Soh, E. Sulaiman, Y. S. Ong,, B. S. Lee, Y. Ren, ‘Grid-based PSE for Engineering of Materials (GPEM)’, CCGrid, pp. 309-316, May 2007.  
  113. D. Lim, Y. S. Ong, Y. Jin and B. Sendhoff, “Trusted Evolutionary Algorithm”, IEEE Congress on Evolutionary Computation, pp. 149- 156, July 16-21, CEC 2006, Sheraton Vancouver Wall Centre, Vancouver, BC, Canada. Available here as PDF file.  
  114. Y. S. Ong,, Z. Z. Zong and D. Lim, “Curse and Blessing of Uncertainty in Evolutionary Algorithm Using Approximation”, IEEE Congress on Evolutionary Computation, pp. 2928 - 2935, July 16-21, CEC 2006, Sheraton Vancouver Wall Centre, Vancouver, BC, Canada. Available here as PDF file.  
  115. Y. S. Ong,, Q. H Nguyen, M. H. Lim and T. Jing, “A Development Platform for Memetic Algorithm Design”, Joint 3rd International Conference on Soft Computing and Intelligent Systems and 7th International Symposium on Advanced Intelligent Systems, SCIS&ISIS 2006, 20-24 September , 2006, O-okayama Campus West Bldg. 9, Tokyo Institute of Technology, Japan.  
  116. J. Tang, M. H. Lim and Y. S. Ong,,, "Adaptation for parallel memetic algorithm based on population entropy", Proceedings of the 8th annual conference on Genetic and Evolutionary Computation (GECCO), Seattle, Washington, USA, pp. 575 - 582, 2006. (Best paper Award Nomination)  
  117. S. D. Handoko, C. K. Kwoh, Y. S. Ong,,, L. Z. Guang and B. Vladimir, "Extreme Learning Machine for Predicting HLA-Peptide Binding", Third International Symposium on Neural Networks, Lecture Notes in Computer Science, vol. 3973, pp.716-721, 2006, Springer-verlag.  
  118. H.K. Ng, D. Lim, Y. S. Ong,, B. S. Lee, L. Freund, S. Parvez and B. Sendhoff, “A Multi-Cluster Grid Enabled Evolution framework for Aerodynamic Airfoil Design Optimization”, International Conference on Natural Computing, 27-29 August 2005, Lecture Notes on Science 3611, pp. 1112-1121, Springer-verlag, L. P. Wang, K. Chen and , Y. S. Ong, Eds. Available here as PDF file.  
  119. Z. Z. Zhou, Y. S. Ong,,, M. H. Nguyen and D. Lim, “A Study on Polynomial Regression and Gaussian Process Global Surrogate Model in Hierarchical Surrogate-Assisted Evolutionary Algorithm”, Special Session on Evolutionary Computation in Dynamic and Uncertain Environments (ECiDUE'05), IEEE Congress on Evolutionary Computation, Edinburgh, United Kingdom, pp. 2832- 2839, Vol. 3, September 2-5, 2005. Available here as PDF file.  
  120. D. Lim, Y. S. Ong,,and B. S. Lee, “Inverse Multi-Objective Robust Evolutionary Design Optimization in the Presence of Uncertainty”, Conference on Genetic and evolutionary computation pp. 55 - 62, June 25-29, 2005. Available here as PDF file.  
  121. J. Tang, M. H. Lim, Y. S. Ong,,and M. J. Er, Solving large scale combinatorial optimization using PMA-SLS, Conference on Genetic and evolutionary computation, pp. 621 - 628, June 25-29, 2005.  
  122. Q. T. Ho, W. T. Cai and Y. S. Ong,,, “Design and Implementation of An Efficient Multi-cluster GridRPC System”, IEEE Cluster Computing and Grid Conference, pp. 358 - 365, 9-12 May 2005.  
  123. H. K. Ng, Y. S. Ong,,, T. Hung and B. S. Lee, “Grid Enabled Optimization”, European Grid Conference, 2005, Lecture Notes in Computer Science, Vol. 3470, pp. 296-304, 2005.  
  124. Q. T. Ho, Y. S. Ong,,, W. T. Cai, H. K. Ng, and B. S. Lee, “GAD Kit - A Toolkit for Gridifying Applications”, Fifth International Conference on Parallel and Distributed Computing, Applications and Technologies, Vol. 3320/2004, pp. 868-871, December 2004. Available here as PDF file.  
  125. Z. X. Zhu, Y. S. Ong,,, K. W. Wong and K. T. Seow, “Experimental Condition Selection In Whole-Genome Functional Classification”, IEEE Conference on Cybernetic and Intelligent System, pp. 295 - 300, Vol.1, December 2004.  
  126. W. B. Song, Y. S. Ong,,, H. K. Ng, A. J. Keane, S. Cox and B. S. Lee, “A Service-Oriented Approach for Aerodynamic Shape Optimization across Institutional Boundaries”, Eighth International Conference on Control, Automation, Robotics and Vision, ICARCV 2004, Special Session on Computational Intelligence on the Grid, pp. 2273-2278, December 6-9, 2004, Kunming, China. Available here as PDF file.  
  127. T. Jing, M. H. Lim and Y. S. Ong,,, “Study of Migration Topology in Island Model Parallel Hybrid-GA for Large Scale Quadratic Assignment Problems”, Eighth International Conference on Control, Automation, Robotics and Vision, ICARCV 2004, Special Session on Computational Intelligence on the Grid, Vol.3, pp. 2286- 2291, December 6-9, 2004, Kunming, China. Available here as PDF file.  
  128. Wong K.W., Y. S. Ong,,, Eren H. and Fung C.C., “Hybrid Fuzzy Modelling Using Memetic Algorithm for Hydrocyclone Control”, Proceedings of the 2004 International Conference on Machine learning and Cybernetics, pp. 4188-4192, 26-29 August 2004, Shanghai, China. Available here as PDF file.  
  129. H. K. Ng, Y. S. Ong,,, T. Hung and B. S. Lee, “Complex Engineering Design Problem Solving Environment Grid Portal”, 2nd International Conference on Scientific and Engineering Computation, July 2004, Singapore. Available here as PDF file.  
  130. Z. Z. Zhou, Y. S. Ong,,and P. B. Nair, “Hierarchical Surrogate-Assisted Evolutionary Optimization Framework”, IEEE Congress on Evolutionary Computation, Special Session on Learning and Approximation in Design Optimization, Portland, USA, pp. 1586 - 1593, Vol.2, June 20-23, 2004. Available here as PDF file.  
  131. Q. T. Ho, Y. S. Ong,,, W. T. Cai, “Gridifying Aerodynamic Design Problem Using GridRPC”, Second Grid and Cooperative Computing: Second International Workshop, GCC 2003, Shanghai, China, December 7-10, 2003, Lecture Notes in Computer Science, Springer-Verlag Heidelberg, Part I, Subject: Computer Science, Volume 3032 / 2004, editors: Minglu Li, Xian-He Sun, Qianni Deng, et al., pp. 83 - 90, Online Date: April 2004.  Available here as PS file.  
  132. S. K. Ng, Z. X. Zhu and Y. S. Ong,,,  “Whole-Genome Functional Classification of Genes by Latent Semantic Analysis on Microarray  Data”, 2nd Asia-Pacific Bioinformatics Conference (APBC2004), pp. 123 - 129, Vol. 29, Dunedin, New Zealand, 18 - 22 Jan 2004. Available here as PDF file.  
  133. K. W. Wong, Y. S. Ong,,, T. D. Gedeon and C. C. Fung, “Intelligent Well Log Data Analysis for Reservoir Characterization”, Fourth International Conference on Intelligent Technologies, pp. 203-208, December 17-19, 2003, Thailand, Chiang Mai.  
  134. Z. Ning, Y. S. Ong,,, K. W. Wong and K. T. Seow, “Parameter Identification Using Memetic Algorithms for Fuzzy Systems”, Fourth International Conference on Intelligent Technologies, pp. 4188 - 4193, Vol.7, 17-19 December 2003, Thailand, Chiang Mai. Available here as PDF file.  
  135. T. Jing, M. H. Lim and Y. S. Ong,,, “Island Model Parallel Hybrid-GA for Large Scale Combinatorial Optimization”, 2nd International Conference on Computational Intelligence, Robotics and Autonomous Systems (CIRAS 2003), Special Session on Optimization using Genetic, Evolutionary, Social and Behavioral Algorithms, pp. 621 - 628, December 15-18, 2003, Singapore. Available here as PDF file.  
  136. Z. Ning, Y. S. Ong,,, K. W. Wong and M. H. Lim, “Choice of Memes In Memetic Algorithm”, 2nd International Conference on Computational Intelligence, Robotics and Autonomous Systems (CIRAS 2003), Special Session on Optimization using Genetic, Evolutionary, Social and Behavioral Algorithms, December 15-18, 2003, Singapore. Available here as PDF file.  
  137. A. Agarwal, Y. L. Xu, M. H. Lim and Y. S. Ong,,, ''Evolutionary Graph Mining for the Discovery of Site Visitation Sequences for a Single URAV'', 2nd International Conference on Computational Intelligence, Robotics and Autonomous Systems, 2003.  
  138. T. Jing, M. H. Lim and Y. S. Ong,,, “A Parallel Hybrid GA for Combinatorial Optimization Using Grid Technology”, IEEE Congress on Evolutionary Computation, pp. 1895 - 1902, Vol.3, December 8-12, 2003, Canberra, Australia. Available here as PDF file.  
  139. D. M. Shi, Y. S. Ong,,and E. C. Tan, “Handwritten Chinese Character Recognition Using Kernel Active Handwriting Model”, IEEE International Conference on Systems, Man & Cybernetics, pp. 251 - 255, Vol.1, 5-8 October 2003, Washington, D.C., USA.  
  140. A. Choudhury, Y. S. Ong,,and A.J. Keane, “Extracting Latent Structures in Numerical Classification: An investigation using two factor models”, 9th International Conference on Neural Information Processing, 18-22 November, pp. 1842 - 1846, Vol.4, 2002.  
  141. Alfred C. H. Tan, A. Choudhury, Y. S. Ong,, and S. Veres, “Ultra Low Frequency Estimation: A Neglected Apportion”, 9th International Conference on Neural Information Processing, Vol. 5, pp. 2195- 2199, 18-22 November 2002.   
  142. Y. S. Ong,, A.J. Keane and P.B. Nair, “Surrogate-Assisted Coevolutionary Search”, 9th International Conference on Neural Information Processing, Special Session on Trends in Global Optimization, pp. 1140 - 1145, Vol.3, 18-22 November 2002. Available here as PS file.  
  143. Y. S. Ong, and A.J. Keane, “An Automated Optimization System for Aircraft Wing Design”, Seventh International Conference on Artificial Intelligence in Design, Cambridge, UK, July 2002. 
  144. Q. Bin, Y. S. Ong,,, Y. Liu, H. B. Gooi and S. Chen, “Managing Metadata over the WWW Using Extensible Markup Language (XML)”, IEEE PES Power Engineering Society Winter Meeting, New York, USA, January, 2002.  
  145. Y. S. Ong, and H. B. Gooi, “A Web-Based Power Flow Simulator for Power Engineering Education”, IEEE PES Power Engineering Society Summer Meeting, Edmonton, Canada, July, 1999.  

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