Cover Image

Pareto Front Shape-Agnostic Pareto Set Learning in Multi-Objective Optimization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ye, Rongguang, Chen, Longcan, Kou, Wei-Bin, Zhang, Jinyuan, Ishibuchi, Hisao
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Collaborative Pareto Set Learning in Multiple Multi-Objective Optimization Problems
by: Shang, Chikai, et al.
Published: (2024)

Evolutionary Preference Sampling for Pareto Set Learning
by: Ye, Rongguang, et al.
Published: (2024)

Data-Driven Preference Sampling for Pareto Front Learning
by: Ye, Rongguang, et al.
Published: (2024)

Efficient First-Order Optimization on the Pareto Set for Multi-Objective Learning under Preference Guidance
by: Chen, Lisha, et al.
Published: (2025)

Preference-Optimized Pareto Set Learning for Blackbox Optimization
by: Haishan, Zhang, et al.
Published: (2024)

Traversing Pareto Optimal Policies: Provably Efficient Multi-Objective Reinforcement Learning
by: Qiu, Shuang, et al.
Published: (2024)

Learning Pareto Set for Multi-Objective Continuous Robot Control
by: Shu, Tianye, et al.
Published: (2024)

A Hyper-Transformer model for Controllable Pareto Front Learning with Split Feasibility Constraints
by: Tuan, Tran Anh, et al.
Published: (2024)

Fairness-informed Pareto Optimization : An Efficient Bilevel Framework
by: Tanji, Sofiane, et al.
Published: (2026)

Scalable Min-Max Optimization via Primal-Dual Exact Pareto Optimization
by: Park, Sangwoo, et al.
Published: (2025)

Random Pareto front surfaces
by: Tu, Ben, et al.
Published: (2024)

Reconstructing Physics-Informed Machine Learning for Traffic Flow Modeling: a Multi-Gradient Descent and Pareto Learning Approach
by: Lei, Yuan-Zheng, et al.
Published: (2025)

MOSS: Multi-Objective Optimization for Stable Rule Sets
by: Liu, Brian, et al.
Published: (2025)

C-MORL: Multi-Objective Reinforcement Learning through Efficient Discovery of Pareto Front
by: Liu, Ruohong, et al.
Published: (2024)

qPOTS: Efficient batch multiobjective Bayesian optimization via Pareto optimal Thompson sampling
by: Renganathan, Ashwin, et al.
Published: (2023)

Multiobjective Optimization under Uncertainties using Conditional Pareto Fronts
by: Trappler, Victor, et al.
Published: (2025)

Distributionally Robust Multi-Objective Optimization
by: Yang, Yufeng, et al.
Published: (2026)

Multi-Objective Optimization-Based Anonymization of Structured Data for Machine Learning Application
by: Wei, Yusi, et al.
Published: (2025)

Optimal Distribution of Solutions for Crowding Distance on Linear Pareto Fronts of Two-Objective Optimization Problems
by: Ishibuchi, Hisao, et al.
Published: (2025)

Aligned Multi Objective Optimization
by: Efroni, Yonathan, et al.
Published: (2025)

Preferential Multi-Objective Bayesian Optimization
by: Astudillo, Raul, et al.
Published: (2024)

Enhancing Multi-Objective Optimization through Machine Learning-Supported Multiphysics Simulation
by: Botache, Diego, et al.
Published: (2023)

Pareto Set Characterization in Constrained Multiobjective Optimization and the COBI Problem Generator *
by: Auger, Anne, et al.
Published: (2026)

FERERO: A Flexible Framework for Preference-Guided Multi-Objective Learning
by: Chen, Lisha, et al.
Published: (2024)

ROBBO: An Efficient Method for Pareto Front Estimation with Guaranteed Accuracy
by: Boffadossi, Roberto, et al.
Published: (2025)

Convergence Analysis of the Lion Optimizer in Centralized and Distributed Settings
by: Jiang, Wei, et al.
Published: (2025)

Multi-Objective Optimization for Sparse Deep Multi-Task Learning
by: Hotegni, S. S., et al.
Published: (2023)

Knowledge Gradient for Multi-Objective Bayesian Optimization with Decoupled Evaluations
by: Buckingham, Jack M., et al.
Published: (2023)

Multi-Objective Optimization via Wasserstein-Fisher-Rao Gradient Flow
by: Ren, Yinuo, et al.
Published: (2023)

Algorithms and Differential Game Representations for Exploring Nonconvex Pareto Fronts in High Dimensions
by: Liu, Shanqing, et al.
Published: (2026)

Chebyshev Center-Based Direction Selection for Multi-Objective Optimization and Training PINNs
by: Yoon, Hoyeol, et al.
Published: (2026)

Computing the Pareto Front by Polynomial Elimination, With an Application From System Identification
by: van Rooij, Hans, et al.
Published: (2026)

Worst-Case Complexity of High-Order Algorithms for Pareto-Front Reconstruction
by: Cristofari, Andrea, et al.
Published: (2025)

Locally Adaptive Multi-Objective Learning
by: Kaur, Jivat Neet, et al.
Published: (2026)

Jacobian Descent for Multi-Objective Optimization
by: Quinton, Pierre, et al.
Published: (2024)

A Two-Phase Adaptive Balanced Penalty Method for Controllable Pareto Front Learning under Split Feasibility Conditions
by: Hoang, Nguyen Viet, et al.
Published: (2026)

Optimization over Sparse Support-Preserving Sets: Two-Step Projection with Global Optimality Guarantees
by: de Vazelhes, William, et al.
Published: (2025)

Gradient Descent is Pareto-Optimal in the Oracle Complexity and Memory Tradeoff for Feasibility Problems
by: Blanchard, Moise
Published: (2024)

Data-driven Mixed Integer Optimization through Probabilistic Multi-variable Branching
by: Chen, Yanguang, et al.
Published: (2023)

Computing the Exact Pareto Front in Average-Cost Multi-Objective Markov Decision Processes
by: Luo, Jiping, et al.
Published: (2026)