Decision Support Systems
Models and tools that help people make well-informed decisions in complex, uncertain settings.
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Voronoi-grid-based Pareto Front Learning and Its Application to Collaborative Federated Learning
M Chen, X Wu, Q Liu, T He, YS Ong, Y Jin, Q Lao, H Yu
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Uncertain Multi-Objective Recommendation via Orthogonal Meta-Learning Enhanced Bayesian Optimization
H Wang, Z Sun, Y Du, L Zhang, T He, YS Ong
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SiamNAS: Siamese Surrogate Model for Dominance Relation Prediction in Multi-objective Neural Architecture Search
Y Zhou, F Neri, YS Ong, R Bai. Cited by 2
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Scalable Cold-Start Optimization in Serverless Computing: Leveraging Function Fusion with PanOpticon Simulator
RK Behera, A Kumari, SB Cho
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Regression and relation-assisted evolutionary algorithm for high-dimensional expensive multi-objective optimization
S Zhu, Y Zhang, W Fang, M Cui, K Deb. Cited by 2
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Ranking-prediction based evolutionary algorithm for expensive many-objective optimization problems
Y Zhang, S Zhu, W Fang, K Deb, M Cui
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Quality Diversity Genetic Programming for Learning Scheduling Heuristics
M Xu, F Neumann, A Neumann, YS Ong. Cited by 2
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Progressive Surrogate Modeling for a Multi-objective Competitive Co-evolutionary (MoCCoEv) Wargame Strategy Optimization
R Guha, R Mckendrick, B Feest, K Deb
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Pareto Set Learning through Genetic Programming for Multi-Objective Dynamic Scheduling
M Xu, Y Mei, F Zhang, YS Ong, M Zhang
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Multi-Objective Competitive Co-Evolutionary Optimization and Regularity-Based Decision-Making for two-Agent Wargame Strategy Optimization
R Guha, R Mckendrick, B Feest, K Deb
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Machine Learning-Driven Preventive Maintenance for Fibreboard Production in Industry 4.0
S Suwatcharachaitiwong, N Sirivongpaisal, T Surasak, N Jiteurtragool, et al
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Machine Learning-Assisted Constraint Handling Under Variable Uncertainty for Preference-based Multi-Objective Optimization
D Yadav, P Ramu, K Deb