Multi-objective Optimization

Posted:   October 05, 2022

Status:   Completed

Tags :   summary

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

Algorithms

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] [PPT]  
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 UAI 2022 Ye st al. [paper] [code]  
12. A Multi-objective Multi-task Learning Framework Induced by Pareto Stationarity ICML 2022 Momma st al. [paper]  
13. Generalization In Multi-Objective Machine Learning arxiv 2022 Súkeník st al. [paper]  
14. Multi-objective Optimization by Learning Space Partition ICLR 2022 Zhao st al. [paper] [open]  
15. A Two-Stage Neural-Filter Pareto Front Extractor and the need for Benchmarking ICLR_Reject 2022 Gupta st al. [paper] [open]  

Applications

| Paper Title | Venue | Year | Authors | Materials | Comment | | ———————————————————— | —– | —- | ————– | ———————————————————— | ———————————————————— | | 1. A pareto-efficient algorithm for multiple objective optimization in e-commerce recommendation| RecSys | 2019 | Lin st al. | [paper] | | | 2. Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Control| ICML | 2020 | Xu st al. | [paper] [code] | | | 3. Controllable Dynamic Multi-Task Architectures| CVPR | 2022 | Raychaudhuri st al. | [paper] [code] | | | 4. Pareto Policy Adaptation| ICLR | 2022 | Kyriakis st al. | [paper] [open] | | | 5. Pareto Set Learning for Neural Multi-Objective Combinatorial Optimization| ICLR | 2022 | Lin st al. | [paper] [open] [code] | | | 6. Pareto Policy Pool for Model-based Offline Reinforcement Learning| ICLR | 2022 | Yang st al. | [paper] [open] [code] | | | 7. Multi-Objective Online Learning| ICLR_Reject | 2022 | Jiang st al. | [paper] [open] [code] | | | 8. On Multi-objective Policy Optimization as a Tool for Reinforcement Learning: Case Studies in Offline RL and Finetuning| ICLR_Reject | 2022 | Abdolmaleki st al. | [paper] [open] | | | 9. Multi-Objective Model Selection for Time Series Forecasting | ICLR_Reject | 2022 | Borchert st al. | [paper] [open] | | | 10. Multi-Objective Meta Learning | NIPS | 2022 | Ye st al. | [paper] [open] [code]| |

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