Cover Image

Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chen, Weiyu, Lin, Baijiong, Zhang, Xiaoyuan, Lin, Xi, Zhao, Han, Zhang, Qingfu, Kwok, James T.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

PMGDA: A Preference-based Multiple Gradient Descent Algorithm
by: Zhang, Xiaoyuan, et al.
Published: (2024)

LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorch
by: Zhang, Xiaoyuan, et al.
Published: (2024)

UMOEA/D: A Multiobjective Evolutionary Algorithm for Uniform Pareto Objectives based on Decomposition
by: Zhang, Xiaoyuan, et al.
Published: (2024)

A First-Order Multi-Gradient Algorithm for Multi-Objective Bi-Level Optimization
by: Ye, Feiyang, et al.
Published: (2024)

Pareto Merging: Multi-Objective Optimization for Preference-Aware Model Merging
by: Chen, Weiyu, et al.
Published: (2024)

RouterDC: Query-Based Router by Dual Contrastive Learning for Assembling Large Language Models
by: Chen, Shuhao, et al.
Published: (2024)

Smooth Tchebycheff Scalarization for Multi-Objective Optimization
by: Lin, Xi, et al.
Published: (2024)

BYOM: Building Your Own Multi-Task Model For Free
by: Jiang, Weisen, et al.
Published: (2023)

Efficient Pareto Manifold Learning with Low-Rank Structure
by: Chen, Weiyu, et al.
Published: (2024)

Few for Many: Tchebycheff Set Scalarization for Many-Objective Optimization
by: Lin, Xi, et al.
Published: (2024)

Quality-Diversity Optimization as Multi-Objective Optimization
by: Lin, Xi, et al.
Published: (2026)

PARM: Multi-Objective Test-Time Alignment via Preference-Aware Autoregressive Reward Model
by: Lin, Baijiong, et al.
Published: (2025)

Dual-Balancing for Multi-Task Learning
by: Lin, Baijiong, et al.
Published: (2023)

Adaptive Online Mirror Descent for Tchebycheff Scalarization in Multi-Objective Learning
by: Liu, Meitong, et al.
Published: (2024)

Fine-tuning Large Language Model for Automated Algorithm Design
by: Liu, Fei, et al.
Published: (2025)

CoEvo: Continual Evolution of Symbolic Solutions Using Large Language Models
by: Guo, Ping, et al.
Published: (2024)

Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization
by: Liu, Fei, et al.
Published: (2024)

Attention-Based Sampler for Diffusion Language Models
by: Zhou, Yuyan, et al.
Published: (2026)

Tackling the Non-IID Issue in Heterogeneous Federated Learning by Gradient Harmonization
by: Zhang, Xinyu, et al.
Published: (2023)

FoMEMO: Towards Foundation Models for Expensive Multi-objective Optimization
by: Yao, Yiming, et al.
Published: (2025)

Learning to Reduce Search Space for Generalizable Neural Routing Solver
by: Zhou, Changliang, et al.
Published: (2025)

Pareto Continual Learning: Preference-Conditioned Learning and Adaption for Dynamic Stability-Plasticity Trade-off
by: Lai, Song, et al.
Published: (2025)

Joint Optimization of Multi-Objective Reinforcement Learning with Policy Gradient Based Algorithm
by: Bai, Qinbo, et al.
Published: (2021)

Latent-Conditioned Policy Gradient for Multi-Objective Deep Reinforcement Learning
by: Kanazawa, Takuya, et al.
Published: (2023)

Beyond Scaleup: Knowledge-aware Parsimony Learning from Deep Networks
by: Yao, Quanming, et al.
Published: (2024)

Multi-Objective Reward and Preference Optimization: Theory and Algorithms
by: Agnihotri, Akhil
Published: (2025)

Few-for-Many Personalized Federated Learning
by: Guo, Ping, et al.
Published: (2026)

Scalable Multi-Objective and Meta Reinforcement Learning via Gradient Estimation
by: Zhang, Zhenshuo, et al.
Published: (2025)

Multiple Wasserstein Gradient Descent Algorithm for Multi-Objective Distributional Optimization
by: Nguyen, Dai Hai, et al.
Published: (2025)

Multi-Objective Bilevel Learning
by: Zhang, Zhiyao, et al.
Published: (2025)

Self-Improved Learning for Scalable Neural Combinatorial Optimization
by: Luo, Fu, et al.
Published: (2024)

Rethinking LLM Unlearning Objectives: A Gradient Perspective and Go Beyond
by: Wang, Qizhou, et al.
Published: (2025)

Multi-Objective Adaptive Rate Limiting in Microservices Using Deep Reinforcement Learning
by: Lyu, Ning, et al.
Published: (2025)

Robust and Efficient Deep Hedging via Linearized Objective Neural Network
by: Zhao, Lei, et al.
Published: (2025)

Deep Multi-Objective Reinforcement Learning for Utility-Based Infrastructural Maintenance Optimization
by: van Remmerden, Jesse, et al.
Published: (2024)

Effective Policy Learning for Multi-Agent Online Coordination Beyond Submodular Objectives
by: Zhang, Qixin, et al.
Published: (2025)

Prompt Learning for Generalized Vehicle Routing
by: Liu, Fei, et al.
Published: (2024)

The Definitive Guide to Policy Gradients in Deep Reinforcement Learning: Theory, Algorithms and Implementations
by: Lehmann, Matthias
Published: (2024)

L-AutoDA: Leveraging Large Language Models for Automated Decision-based Adversarial Attacks
by: Guo, Ping, et al.
Published: (2024)

RAIN-Merging: A Gradient-Free Method to Enhance Instruction Following in Large Reasoning Models with Preserved Thinking Format
by: Huang, Zhehao, et al.
Published: (2026)