A collection of Awesome papers on Pareto Front Learning, Pareto Multi Task Learning, Multiple Gradient Descent methods to solve Multi-Objective Optimization, Multi-Task Learning as Multi-Objective Optimization, and Optimization in Pareto Set.
- Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Approach [ICLR 2023] [code]
- Independent Component Alignment for Multi-Task Learning [CVPR 2023] [code]
- Stochastic Multiple Target Sampling Gradient Descent [NeurIPS 2022] [code]
- Multi-Task Learning as a Bargaining Game [ICML 2022] [code]
- Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning [TMLR 2022] [code]
- A Multi-objective / Multi-task Learning Framework Induced by Pareto Stationarity [ICML 2022]
- Profiling Pareto Front With Multi-Objective Stein Variational Gradient Descent [NeurIPS 2021 (Spotlight)] [code]
- Conflict-Averse Gradient Descent for Multi-task Learning [NeurIPS 2021] [code]
- Towards Impartial Multi-task Learning [ICLR 2021] [code]
- Controllable Pareto Multi-Task Learning [Arxiv 2021] [code]
- Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models [ICLR 2021] [code]
- Multi-Task Learning with User Preferences Gradient Descent with Controlled Ascent in Pareto Optimization [ICML 2020] [code]
- Gradient Surgery for Multi-Task Learning [NeurIPS 2020] [code]
- Pareto Multi-Task Learning [NeurIPS 2019] [code]
- A Framework for Controllable Pareto Front Learning with Completed Scalarization Functions and its Applications [Arxiv 2023] [code]
- Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models [ICML 2023] [code]
- Improving Pareto Front Learning via Multi-Sample Hypernetworks [AAAI 2023] [code]
- Pareto Set Learning for Neural Multi-Objective Combinatorial Optimization [ICLR 2022][code]
- Pareto Set Learning for Expensive Multi-Objective Optimization [NeurIPS 2022][code]
- Multi-Objective Learning to Predict Pareto Fronts Using Hypervolume Maximization [Arxiv 2021] [code]
- Self-Evolutionary Optimization for Pareto Front Learning [Arxiv 2021]
- Learning the Pareto Front with Hypernetworks [ICLR 2021][code]
- Scalable Pareto Front Approximation for Deep Multi-Objective Learning [ICDM 2021] [code]
- Pareto Navigation Gradient Descent: a First-Order Algorithm for Optimization in Pareto Set [UAI 2022][code]
- Pareto Efficient Fairness in Supervised Learning: From Extraction to Tracing [Arxiv 2021]
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