/Multi-objective-optimization-and-Multi-task-Learning

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]
16. Improving Pareto Front Learning via Multi-Sample Hypernetworks AAAI 2023 Hoang st al. [paper]
17. A Framework for Controllable Pareto Front Learning with Completed Scalarization Functions and its Applications arxiv 2023 Tuan st al. [paper]
18. Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models ICML 2023 Dimitriadis st al. [paper] [code]
19. Multi-objective Learning Using HV Maximization EMO 2023 Deist st al. [paper] [code]

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]
11. On the Pareto Front of Multilingual Neural Machine Translation arxiv 2023 Chen st al. [paper] [code]

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