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A Collection of Main Papers on Gradient-based-Multi-objective-optimization-and-Deep-Multi-task-Learning

Paper Title Venue Year Authors Materials Comment
1. Multi-Task Learning as Multi-Objective Optimization NIPS 2018 Sener et al. [paper] [code] [blog]
2. Pareto Multi-Task Learning NIPS 2019 Lin st al. [paper] [code] [blog]
3. Effcient Continuous Pareto Exploration in Multi-Task Learning ICML 2020 Ma st al. [paper][code] [blog]
4. Multi-Task Learning with User Preferences Gradient Descent with Controlled Ascent in Pareto Optimization ICML 2020 Mahapatra st al. [paper] [code]
5. Controllable Pareto Multi-Task Learning arxiv 2021 Lin st al. [paper]
6. Learning the pareto front with hypernetworks ICLR 2021 Navon st al. [paper] [code]
7. Profiling Pareto Front With Multi-Objective Stein Variational Gradient Descent NIPS 2021 Liu st al. [paper] [code]
8. Scalable Pareto Front Approximation for Deep Multi-Objective Learning ICDM 2021 Ruchte st al. [paper] [code]
9. Multi-Objective Learning to Predict Pareto Fronts Using Hypervolume Maximization arxiv 2021 Deist st al. [paper] [code]
10. Self-Evolutionary Optimization for Pareto Front Learning arxiv 2021 Chang st al. [paper]
11. Pareto Navigation Gradient Descent: a First-Order Algorithm for Optimization in Pareto Set arXiv 2021 Ye st al. [paper]

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